Difference between revisions of "Example Models and Libraries - Table"
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This page lists example models and libraries. You can download them from here or (in some cases) link to a page with more details. Feel free to include and upload your own models and libraries. | This page lists example models and libraries. You can download them from here or (in some cases) link to a page with more details. Feel free to include and upload your own models and libraries. | ||
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! scope="col" style="min-width: 100px; max-width: 120px;" |Download | ! scope="col" style="min-width: 100px; max-width: 120px;" |Download | ||
! Domain | ! Domain | ||
+ | ! Methods | ||
! style="min-width: 300px;" | Description | ! style="min-width: 300px;" | Description | ||
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! For more | ! For more | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Marginal abatement home heating.ana|Marginal abatement home heating.ana]] |
|carbon price, energy efficiency, climate policy | |carbon price, energy efficiency, climate policy | ||
+ | |graph methods, optimal allocation, budget constraint | ||
|<div style="text-align: left;">Shows how to set up a Marginal Abatement graph in Analytica.</div> | |<div style="text-align: left;">Shows how to set up a Marginal Abatement graph in Analytica.</div> | ||
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|[[Marginal Abatement Graph]] | |[[Marginal Abatement Graph]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Solar Panel Analysis.ana|Solar Panel Analysis.ana]] |
|renewable energy, photovoltaics, tax credits | |renewable energy, photovoltaics, tax credits | ||
+ | |net present value, internal rate of return, agile modeling | ||
|<div style="text-align: left;">Explores whether it would it be cost effective to install solar panels on the roof of a house in San Jose, California.</div> | |<div style="text-align: left;">Explores whether it would it be cost effective to install solar panels on the roof of a house in San Jose, California.</div> | ||
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|[[Solar Panel Analysis]] | |[[Solar Panel Analysis]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[Media: | + | |[[Media:Items within budget.ana|Items within budget.ana]] |
+ | | | ||
| | | | ||
|<div style="text-align: left;">Given a set of items, with a priority and a cost for each, selects out the highest priority items that fit within the fixed budget. </div> | |<div style="text-align: left;">Given a set of items, with a priority and a cost for each, selects out the highest priority items that fit within the fixed budget. </div> | ||
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|[[Items within Budget function]] | |[[Items within Budget function]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[Media: | + | |[[Media:Grant exclusion.ANA|Grant exclusion.ana]] |
|business analysis | |business analysis | ||
+ | | | ||
|<div style="text-align: left;">Tests a hypothesis about the distribution of an attribute of the marginal rejectee of a grant program, given the relevance of that attribute to award of the grant.</div> | |<div style="text-align: left;">Tests a hypothesis about the distribution of an attribute of the marginal rejectee of a grant program, given the relevance of that attribute to award of the grant.</div> | ||
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|[[Grant Exclusion Model]] | |[[Grant Exclusion Model]] | ||
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|[[Media:Project Priorities 5 0.ana|Project Priorities 5 0.ana]] | |[[Media:Project Priorities 5 0.ana|Project Priorities 5 0.ana]] | ||
|business models | |business models | ||
+ | |cost analysis, net present value (NPV), uncertainty analysis | ||
|<div style="text-align: left;">Evaluates a set of R&D projects (including uncertain R&D costs/revenues), uses multiattribute analysis to compare projects & generates the best portfolio given a R&D budget.</div> | |<div style="text-align: left;">Evaluates a set of R&D projects (including uncertain R&D costs/revenues), uses multiattribute analysis to compare projects & generates the best portfolio given a R&D budget.</div> | ||
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|[[Project Planner]] | |[[Project Planner]] | ||
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| Model | | Model | ||
|[[Media:Steel and aluminum tariff model.ana|Steel and aluminum tariff model.ana]] | |[[Media:Steel and aluminum tariff model.ana|Steel and aluminum tariff model.ana]] | ||
+ | | | ||
| | | | ||
| <div style="text-align: left;">Estimate of the net impact of the 2018 import tariffs on steel and aluminum on the US trade deficit.</div> | | <div style="text-align: left;">Estimate of the net impact of the 2018 import tariffs on steel and aluminum on the US trade deficit.</div> | ||
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|[[Steel and Aluminum import tariff impact on US trade deficit]] | |[[Steel and Aluminum import tariff impact on US trade deficit]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[Media: Tax bracket interpolation 2021.ana|Tax bracket interpolation 2021.ana]] | + | |[[Media:Tax bracket interpolation 2021.ana|Tax bracket interpolation 2021.ana]] |
+ | | | ||
| | | | ||
|<div style="text-align: left;">Computes amount of tax due from taxable income for a 2017 US Federal tax return.</div> | |<div style="text-align: left;">Computes amount of tax due from taxable income for a 2017 US Federal tax return.</div> | ||
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|[[Tax bracket interpolation]] | |[[Tax bracket interpolation]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[Media: | + | |[[Media:Feasible Sampler.ana|Feasible Sampler.ana]] |
|feasibility | |feasibility | ||
+ | | | ||
|<div style="text-align: left;">Implements a button that will sample a collection of chance variables, then reset the sample size and keep only those sample points that are "feasible".</div> | |<div style="text-align: left;">Implements a button that will sample a collection of chance variables, then reset the sample size and keep only those sample points that are "feasible".</div> | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Cross-validation example.ana|Cross-validation example.ana]] |
| | | | ||
+ | |cross-validation, overfitting, non-linear kernel functions | ||
|<div style="text-align: left;">Fits a non-linear kernel function to the residual error, and uses cross-validation to determine how many kernel functions should be used.</div> | |<div style="text-align: left;">Fits a non-linear kernel function to the residual error, and uses cross-validation to determine how many kernel functions should be used.</div> | ||
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|[[Cross-Validation / Fitting Kernel Functions to Data]] | |[[Cross-Validation / Fitting Kernel Functions to Data]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Bootstrapping.ana|Bootstrapping.ana]] |
| | | | ||
+ | |bootstrapping, sampling error, re-sampling | ||
|<div style="text-align: left;">Bootstrapping; estimates sampling error by resampling the original data.</div> | |<div style="text-align: left;">Bootstrapping; estimates sampling error by resampling the original data.</div> | ||
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|[[Statistical Bootstrapping]] | |[[Statistical Bootstrapping]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Kernel Density Estimation.ana|Kernel Density Estimation.ana]] |
| | | | ||
+ | |kernel density estimation, kernel density smoothing | ||
|<div style="text-align: left;">Demonstrates a very simple fixed-width kernel density estimator to estimate a "smooth" probability density.</div> | |<div style="text-align: left;">Demonstrates a very simple fixed-width kernel density estimator to estimate a "smooth" probability density.</div> | ||
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|[[Smooth PDF plots using Kernel Density Estimation]] | |[[Smooth PDF plots using Kernel Density Estimation]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Output and input columns.ana|Output and input columns.ana]] |
| | | | ||
+ | |data analysis | ||
|<div style="text-align: left;">Presents an input table to a user, where one column is populated with computed output data, the other column with checkboxes for the user to select.</div> | |<div style="text-align: left;">Presents an input table to a user, where one column is populated with computed output data, the other column with checkboxes for the user to select.</div> | ||
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|[[Output and Input Columns in Same Table]] | |[[Output and Input Columns in Same Table]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Platform 2018b.ana|Platform2018b.ana]] |
|offshore platforms, oil and gas, stakeholders, rigs to reefs, decision support | |offshore platforms, oil and gas, stakeholders, rigs to reefs, decision support | ||
+ | |decision analysis, multi-attribute, sensitivity analysis | ||
|<div style="text-align: left;">Determined how to decommission California's 27 offshore oil platforms.</div> | |<div style="text-align: left;">Determined how to decommission California's 27 offshore oil platforms.</div> | ||
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|[[From Controversy to Consensus: California's offshore oil platforms]] | |[[From Controversy to Consensus: California's offshore oil platforms]] | ||
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| Model | | Model | ||
− | |[[ | + | |[[Media:Comparing retirement account types.ana|Comparing retirement account types.ana]] or [[Media:Comparing retirement account types without sensitivity.ana|Free 101 Compatible Version]] |
|401(k), IRA, retirement account, decision analysis, uncertainty | |401(k), IRA, retirement account, decision analysis, uncertainty | ||
+ | |[[MultiTable]]s, sensitivity analysis | ||
|<div style="text-align: left;">Explores tradeoffs between different retirement account types.</div> | |<div style="text-align: left;">Explores tradeoffs between different retirement account types.</div> | ||
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|[[Retirement plan type comparison]] | |[[Retirement plan type comparison]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Plane catching with UI 2020.ANA|Plane catching with UI 2020.ANA]] |
| | | | ||
+ | |decision theory, decision analysis, uncertainty, Monte Carlo simulation, value of information, EVPI, EVIU | ||
|<div style="text-align: left;">Determines when you should leave home to catch an early morning plane departure.</div> | |<div style="text-align: left;">Determines when you should leave home to catch an early morning plane departure.</div> | ||
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|[[Plane Catching Decision with Expected Value of Including Uncertainty]] | |[[Plane Catching Decision with Expected Value of Including Uncertainty]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Marginal Analysis for Control of SO2 Emissions.ana|Marginal Analysis for Control of SO2 Emissions.ana]] |
|environmental engineering | |environmental engineering | ||
+ | |cost-benefit analysis, marginal analysis | ||
|<div style="text-align: left;">Marginal analysis a.k.a. benefit/cost analysis to determine the policy alternative that leads us to the most economically efficient level of cleanup of acid rain from coal-burning electric-generating plants.</div> | |<div style="text-align: left;">Marginal analysis a.k.a. benefit/cost analysis to determine the policy alternative that leads us to the most economically efficient level of cleanup of acid rain from coal-burning electric-generating plants.</div> | ||
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|[[Marginal Analysis for Control of SO2 emissions]] | |[[Marginal Analysis for Control of SO2 emissions]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[Media: | + | |[[Media:Donor Presenter Dashboard II.ANA|Donor-Presenter Dashboard.ana]] |
| | | | ||
+ | |dynamic models, Markov processes | ||
|<div style="text-align: left;">Implements a continuous-time Markov chain in Analytica's discrete-time dynamic simulation environment. It supports immigration to, and emigration from, every node.</div> | |<div style="text-align: left;">Implements a continuous-time Markov chain in Analytica's discrete-time dynamic simulation environment. It supports immigration to, and emigration from, every node.</div> | ||
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|[[Donor/Presenter Dashboard]] | |[[Donor/Presenter Dashboard]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Photosynthesis regulation.ANA|Photosynthesis Regulation.ana]] - main regulation pathways<br />[[Media:Photosystem.ana| Photosystem.ana]] - rough sketch of genetic regulation |
|photosynthesis | |photosynthesis | ||
+ | |dynamic models | ||
|<div style="text-align: left;">A model of how photosynthesis is regulated inside a cyanobacteria. Simulates the concentration levels of key transport molecules along the chain.</div> | |<div style="text-align: left;">A model of how photosynthesis is regulated inside a cyanobacteria. Simulates the concentration levels of key transport molecules along the chain.</div> | ||
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|[[Regulation of Photosynthesis]] | |[[Regulation of Photosynthesis]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Time-series-reindexing.ana|Time-series-reindexing.ana]] |
| | | | ||
+ | |dynamic models, forecasting, time-series re-indexing | ||
|<div style="text-align: left;">Examples of time-series re-indexing.</div> | |<div style="text-align: left;">Examples of time-series re-indexing.</div> | ||
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|[[Time-series re-indexing]] | |[[Time-series re-indexing]] | ||
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| Model | | Model | ||
|[[Media:PostCompression.ana|Post Compression Model]] | |[[Media:PostCompression.ana|Post Compression Model]] | ||
+ | | | ||
| | | | ||
|<div style="text-align: left;">Calculator for computing the maximum load that can be handled by a Douglas Fir - Larch post of a given size, grade, and composition in a construction setting.</div> | |<div style="text-align: left;">Calculator for computing the maximum load that can be handled by a Douglas Fir - Larch post of a given size, grade, and composition in a construction setting.</div> | ||
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|[[Timber Post Compression Load Capacity]] | |[[Timber Post Compression Load Capacity]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Compression Post Load Capacity.ana|Compression Post Load Capacity.ana]] |
| | | | ||
+ | |compression analysis | ||
|<div style="text-align: left;">Computes the load that a Douglas-Fir Larch post can support in compression. Works for different timber types and grades and post sizes.</div> | |<div style="text-align: left;">Computes the load that a Douglas-Fir Larch post can support in compression. Works for different timber types and grades and post sizes.</div> | ||
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|[[Compression Post Load Calculator]] | |[[Compression Post Load Calculator]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Daylighting analyzer.ana|Daylighting analyzer.ana]] |
|engineering | |engineering | ||
+ | |cost-benefits analysis | ||
|<div style="text-align: left;">How to analyze lifecycle costs and savings from daylighting options in building design.</div> | |<div style="text-align: left;">How to analyze lifecycle costs and savings from daylighting options in building design.</div> | ||
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|[[Daylighting Options in Building Design]] | |[[Daylighting Options in Building Design]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[Media: | + | |[[Media:California Power Plants.ANA|California Power Plants.ana]] |
|power plants | |power plants | ||
+ | |edit table, choice menu, pulldown menu, checkbox | ||
|<div style="text-align: left;">Example showing how to use Choice menus and Checkbox inside an Edit table.</div> | |<div style="text-align: left;">Example showing how to use Choice menus and Checkbox inside an Edit table.</div> | ||
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|[[California Power Plants]] | |[[California Power Plants]] | ||
|- | |- | ||
| Model | | Model | ||
− | |Requires Analytica Optimizer<br />[[ | + | |Requires Analytica Optimizer<br />[[Media:Electrical Transmission.ana|Electrical Transmission.ana]] |
|electrical engineering, power generation and transmission | |electrical engineering, power generation and transmission | ||
+ | | | ||
|<div style="text-align: left;">Electrical network model that minimizes total cost of generation and transmission.</div> | |<div style="text-align: left;">Electrical network model that minimizes total cost of generation and transmission.</div> | ||
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|[[Electrical Generation and Transmission]] | |[[Electrical Generation and Transmission]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Time of use pricing.ana|Time of use pricing.ana]] & [[Media:MECOLS0620.xlsx|MECOLS0620.xlsx]]<br />(both files needed) |
|reading from spreadsheets, time-of-use pricing, electricity pricing | |reading from spreadsheets, time-of-use pricing, electricity pricing | ||
+ | | | ||
|<div style="text-align: left;">Time-of-use pricing is a rate tariff model used by utility companies that changes more during times when demand tends to exceed supply.</div> | |<div style="text-align: left;">Time-of-use pricing is a rate tariff model used by utility companies that changes more during times when demand tends to exceed supply.</div> | ||
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|[[Time of Use pricing]] | |[[Time of Use pricing]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Color map.ana|Color map.ana]] |
| | | | ||
+ | |computed cell formatting | ||
|<div style="text-align: left;">A model which highlights [[Cell Format Expression|Cell Formatting]] and [[Computed cell formats|Computed Cell Formats]].</div> | |<div style="text-align: left;">A model which highlights [[Cell Format Expression|Cell Formatting]] and [[Computed cell formats|Computed Cell Formats]].</div> | ||
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|[[Color Map]] | |[[Color Map]] | ||
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| Model | | Model | ||
|[[Media:World cup.ana|World cup.ana]] | |[[Media:World cup.ana|World cup.ana]] | ||
+ | | | ||
| | | | ||
|<div style="text-align: left;">Demonstrates the [[Poisson|Poisson distribution]] to determine why France beat Croatia in 2018.</div> | |<div style="text-align: left;">Demonstrates the [[Poisson|Poisson distribution]] to determine why France beat Croatia in 2018.</div> | ||
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|[[2018 World Cup Soccer final]] | |[[2018 World Cup Soccer final]] | ||
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|[http://AnalyticaOnline.com/Lonnie/resnet18.zip resnet18.zip] | |[http://AnalyticaOnline.com/Lonnie/resnet18.zip resnet18.zip] | ||
|residual network, deep residual learning, image recognition | |residual network, deep residual learning, image recognition | ||
+ | | | ||
|<div style="text-align: left;">Show it an image, and it tries to recognize what it is an image of, classifying it among 1000 possible categories. It uses an 18-layer residual network.</div> | |<div style="text-align: left;">Show it an image, and it tries to recognize what it is an image of, classifying it among 1000 possible categories. It uses an 18-layer residual network.</div> | ||
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|[[Image recognition]] | |[[Image recognition]] | ||
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|[[Media:Month to quarter.ana|Month to quarter.ana]] | |[[Media:Month to quarter.ana|Month to quarter.ana]] | ||
| | | | ||
+ | |aggregation, level of detail, days, weeks, months, quarters, years | ||
|<div style="text-align: left;">Shows how to transform an array from a finer-grain index (e.g., Month) onto a coarser index (e.g., Quarter). We generally refer to this as [[Aggregate|aggregation]].</div> | |<div style="text-align: left;">Shows how to transform an array from a finer-grain index (e.g., Month) onto a coarser index (e.g., Quarter). We generally refer to this as [[Aggregate|aggregation]].</div> | ||
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|[[Transforming Dimensions by transform matrix, month to quarter]] | |[[Transforming Dimensions by transform matrix, month to quarter]] | ||
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|[[Media:Convolution.ana|Convolution.ana]] | |[[Media:Convolution.ana|Convolution.ana]] | ||
| | | | ||
+ | |signal analysis, systems analysis | ||
|<div style="text-align: left;">Contains several examples of convolved functions.</div> | |<div style="text-align: left;">Contains several examples of convolved functions.</div> | ||
− | |||
|[[Convolution]] | |[[Convolution]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Dependency Tracker.ANA| Dependency Tracker.ana]] |
| | | | ||
+ | |dependency analysis | ||
|<div style="text-align: left;">This module tracks dependencies through your model, updating the visual appearance of nodes so that you can quickly visualize the paths by which one variable influences another.</div> | |<div style="text-align: left;">This module tracks dependencies through your model, updating the visual appearance of nodes so that you can quickly visualize the paths by which one variable influences another.</div> | ||
− | |||
|[[Dependency Tracker Module]] | |[[Dependency Tracker Module]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:French-English.ana|French-English.ana]] |
|multi-lingual models | |multi-lingual models | ||
+ | | | ||
|<div style="text-align: left;">Maintains a single influence diagram with Title and Description attributes in both English and French.</div> | |<div style="text-align: left;">Maintains a single influence diagram with Title and Description attributes in both English and French.</div> | ||
− | |||
|[[Multi-lingual Influence Diagram]] | |[[Multi-lingual Influence Diagram]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Parsing XML example.ana|Parsing XML example.ana]] |
|data extraction, xml, DOM parsing | |data extraction, xml, DOM parsing | ||
+ | | | ||
|<div style="text-align: left;">Demonstrates two methods for extracting data: Using a full XML DOM parser, or using regular expressions.</div> | |<div style="text-align: left;">Demonstrates two methods for extracting data: Using a full XML DOM parser, or using regular expressions.</div> | ||
− | |||
|[[Extracting Data from an XML file]] | |[[Extracting Data from an XML file]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Vector Math.ana|Vector Math.ana]] |
| | | | ||
+ | |geospatial analysis, GIS, vector analysis | ||
|<div style="text-align: left;">Functions used for computing geospatial coordinates and distances.</div> | |<div style="text-align: left;">Functions used for computing geospatial coordinates and distances.</div> | ||
− | |||
|[[Vector Math]] | |[[Vector Math]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Total Allowable Removal model with Optimizer.ana| Total Allowable w Optimizer.ana]] or<br />[[Media:Total Allowable Removal model w StepInterp.ana|Total Allowable w StepInterp.ana]] for those without Optimizer |
| | | | ||
+ | |population analysis, dynamic models, optimization analysis | ||
|<div style="text-align: left;">Determines how many fish or animals can be caught (landed) annually so that the probability of the population declining X% in Y years (decline threshold) is less than Z% (risk tolerance).</div> | |<div style="text-align: left;">Determines how many fish or animals can be caught (landed) annually so that the probability of the population declining X% in Y years (decline threshold) is less than Z% (risk tolerance).</div> | ||
− | |||
|[[Total Allowable Harvest]] | |[[Total Allowable Harvest]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Cereal Formulation1.ana|Cereal Formulation1.ana]] |
|product formulation, cereal formulation | |product formulation, cereal formulation | ||
+ | | | ||
|<div style="text-align: left;">Cereal formulation/discrete mixed integer model that chooses product formulations to minimize total ingredient costs.</div> | |<div style="text-align: left;">Cereal formulation/discrete mixed integer model that chooses product formulations to minimize total ingredient costs.</div> | ||
− | |||
|[[Linearizing a discrete NSP]] | |[[Linearizing a discrete NSP]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Neural-Network.ana|Neural Network.ana]] |
|feed-forward neural networks, non-linear regression | |feed-forward neural networks, non-linear regression | ||
+ | |optimization analysis | ||
|<div style="text-align: left;">Models set up to train a 2-layer feedforward sigmoid network to "learn" the concept represented by the data set(s), and then test how well it does across examples not appearing in the training set.</div> | |<div style="text-align: left;">Models set up to train a 2-layer feedforward sigmoid network to "learn" the concept represented by the data set(s), and then test how well it does across examples not appearing in the training set.</div> | ||
− | |||
|[[Neural Network]] | |[[Neural Network]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Earthquake expenses.ana|Earthquake expenses.ana]] |
| | | | ||
+ | |risk analysis, cost analysis | ||
|<div style="text-align: left;">An example of risk analysis with time-dependence and costs shifted over time.</div> | |<div style="text-align: left;">An example of risk analysis with time-dependence and costs shifted over time.</div> | ||
− | |||
|[[Earthquake Expenses]] | |[[Earthquake Expenses]] | ||
|- | |- | ||
| Model | | Model | ||
− | |'''Best used with Analytica Optimizer'''<br />[[ | + | |'''Best used with Analytica Optimizer'''<br />[[Media:Loan policy selection.ANA|Loan policy selection.ana]] |
|creditworthiness, credit rating, default risk | |creditworthiness, credit rating, default risk | ||
+ | |risk analysis | ||
|<div style="text-align: left;">Helps a lender decide optimal credit rating threshold to require and what interest rate (above prime) to charge.</div> | |<div style="text-align: left;">Helps a lender decide optimal credit rating threshold to require and what interest rate (above prime) to charge.</div> | ||
− | |||
|[[Loan Policy Selection]] | |[[Loan Policy Selection]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Hubbard and Seiersen cyberrisk.ana|Hubbard_and_Seiersen_cyberrisk.ana]] |
|cybersecurity risk | |cybersecurity risk | ||
+ | |loss exceedance curve, simulation | ||
|<div style="text-align: left;">Simulates loss exceedance curves for a set of cybersecurity events, the likelihood and probabilistic monetary impact of which have been characterized by system experts.</div> | |<div style="text-align: left;">Simulates loss exceedance curves for a set of cybersecurity events, the likelihood and probabilistic monetary impact of which have been characterized by system experts.</div> | ||
− | |||
|[[Inherent and Residual Risk Simulation]] | |[[Inherent and Residual Risk Simulation]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:Red_State_Blue_State_plot.ana]] |
|map, states | |map, states | ||
+ | |graphing | ||
|<div style="text-align: left;">Example containing the shape outlines for each of the 50 US states, along with a graph that uses color to depict something that varies by state.</div> | |<div style="text-align: left;">Example containing the shape outlines for each of the 50 US states, along with a graph that uses color to depict something that varies by state.</div> | ||
− | |||
|[[Red or blue state]] | |[[Red or blue state]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:COVID Model 2020--03-25.ana|COVID Model 2020--03-25.ana]] |
|covid, covid-19, coronavirus, corona, epidemic | |covid, covid-19, coronavirus, corona, epidemic | ||
+ | | | ||
|<div style="text-align: left;">A systems dynamics style SICR model of the COVID-19 outbreak within the state of Colorado.</div> | |<div style="text-align: left;">A systems dynamics style SICR model of the COVID-19 outbreak within the state of Colorado.</div> | ||
− | |||
|[[COVID-19 State Simulator, a Systems Dynamics approach]] | |[[COVID-19 State Simulator, a Systems Dynamics approach]] | ||
|- | |- | ||
Line 352: | Line 352: | ||
|[[Media:Corona Markov.ana|Corona Markov.ana]] | |[[Media:Corona Markov.ana|Corona Markov.ana]] | ||
|covid, covid-19, coronavirus, corona, epidemic, sensitivity analyses | |covid, covid-19, coronavirus, corona, epidemic, sensitivity analyses | ||
+ | | | ||
|<div style="text-align: left;">Explores the progression of the COVID-19 coronavirus epidemic in the US, and to explore the effects of different levels of social isolation.</div> | |<div style="text-align: left;">Explores the progression of the COVID-19 coronavirus epidemic in the US, and to explore the effects of different levels of social isolation.</div> | ||
− | |||
|[[How social isolation impacts COVID-19 spread in the US - A Markov model approach]] | |[[How social isolation impacts COVID-19 spread in the US - A Markov model approach]] | ||
|- | |- | ||
Line 360: | Line 360: | ||
|[[Media:Modelo Epidemiologoco para el Covid-19 con cuarentena.ana|Modelo Epidemiológoco para el Covid-19 con cuarentena.ana]] | |[[Media:Modelo Epidemiologoco para el Covid-19 con cuarentena.ana|Modelo Epidemiológoco para el Covid-19 con cuarentena.ana]] | ||
|covid, covid-19, coronavirus, corona, epidemic | |covid, covid-19, coronavirus, corona, epidemic | ||
+ | | | ||
|<div style="text-align: left;">Un modelo en cadena de Markov del impacto previsto de la enfermedad coronavirus COVID-19 en el Perú, y del impacto del aislamiento social.</div> | |<div style="text-align: left;">Un modelo en cadena de Markov del impacto previsto de la enfermedad coronavirus COVID-19 en el Perú, y del impacto del aislamiento social.</div> | ||
− | |||
|[[Epidemiological model of COVID-19 for Perú, en español]] | |[[Epidemiological model of COVID-19 for Perú, en español]] | ||
|- | |- | ||
| Model | | Model | ||
− | |[[ | + | |[[Media:COVID-19 Triangle Suppression.ana|COVID-19 Triangle Suppression.ana]] |
|covid, covid-19, coronavirus, corona, epidemic | |covid, covid-19, coronavirus, corona, epidemic | ||
+ | | | ||
|<div style="text-align: left;">Models progression of the COVID-19 pandemic in the US, understanding the amount of time that is required for lock down measures when a suppression strategy is adopted.</div> | |<div style="text-align: left;">Models progression of the COVID-19 pandemic in the US, understanding the amount of time that is required for lock down measures when a suppression strategy is adopted.</div> | ||
− | |||
|[[A Triangle Suppression model of COVID-19]] | |[[A Triangle Suppression model of COVID-19]] | ||
|- | |- | ||
Line 376: | Line 376: | ||
|[[Media:Simple COVID-19.ana|Simple COVID-19.ana]] | |[[Media:Simple COVID-19.ana|Simple COVID-19.ana]] | ||
|covid, covid-19, coronavirus, corona, epidemic | |covid, covid-19, coronavirus, corona, epidemic | ||
+ | | | ||
|<div style="text-align: left;">Explores possible COVID-19 Coronavirus scenarios from the beginning of March, 2020 through the end of 2020 in the US.</div> | |<div style="text-align: left;">Explores possible COVID-19 Coronavirus scenarios from the beginning of March, 2020 through the end of 2020 in the US.</div> | ||
− | |||
|[[COVID-19 Coronavirus SICR progression for 2020]] | |[[COVID-19 Coronavirus SICR progression for 2020]] | ||
|- | |- | ||
Line 384: | Line 384: | ||
|[[Media:US COVID-19 Data.ana|US COVID-19 Data.ana]] | |[[Media:US COVID-19 Data.ana|US COVID-19 Data.ana]] | ||
|covid, covid-19, coronavirus, corona, epidemic, death, infection | |covid, covid-19, coronavirus, corona, epidemic, death, infection | ||
+ | | | ||
|<div style="text-align: left;">Reads in [https://github.com/nytimes/covid-19-data COVID-19 data from the New York Times] and transforms it into a form that is convenient to work with in Analytica.</div> | |<div style="text-align: left;">Reads in [https://github.com/nytimes/covid-19-data COVID-19 data from the New York Times] and transforms it into a form that is convenient to work with in Analytica.</div> | ||
− | |||
|[[COVID-19 Case and Death data for US states and counties]] | |[[COVID-19 Case and Death data for US states and counties]] | ||
|- | |- | ||
Line 392: | Line 392: | ||
|[[Media:Voluntary vs mandatory testing.ana|Voluntary vs mandatory testing.ana]] | |[[Media:Voluntary vs mandatory testing.ana|Voluntary vs mandatory testing.ana]] | ||
|covid, covid-19, coronavirus, corona, epidemic | |covid, covid-19, coronavirus, corona, epidemic | ||
+ | | | ||
|<div style="text-align: left;">Computes the rate of infection in scenarios when COVID-19 testing is required/optional,based on prevalence rates, test accuracies and voluntary testing rates.</div> | |<div style="text-align: left;">Computes the rate of infection in scenarios when COVID-19 testing is required/optional,based on prevalence rates, test accuracies and voluntary testing rates.</div> | ||
+ | |[[Mandatory vs Voluntary testing policies]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Takes typical bond purchase inputs (purchase price, par value, interest rate, and life to maturity) and calculates bond cash flows, current yield, and yield to maturity.</div> | ||
+ | |[[Bond Model]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Example of a breakeven analysis of a set of revenue levels, when the fixed expenses are set at one amount and the variable expenses are a constant fraction of revenue.</div> | ||
+ | |[[Breakeven Analysis]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Evaluates and compares the expected commercialization value of multiple proposed R&D projects.</div> | ||
+ | |[[Expected R&D Project Value]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Financial Statement Templates]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Explores a market for a new product, and the pricing and advertising budget decisions involved.</div> | ||
+ | |[[Market Model]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Takes input data for activity paths required to complete a project, and calculates various outputs describing the critical path, timing, and costs for project completion.</div> | ||
+ | |[[Plan_Schedule_ Control]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Evaluates and prioritizes a portfolio of projects based on either the estimated net present value or a multi-attribute score, based on strategy fit, staff development, the generation of public goodwill, and estimated net revenue.</div> | ||
+ | |[[Project Portfolio Planner]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Sales Effectiveness]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
| | | | ||
− | |[[ | + | |<div style="text-align: left;"></div> |
+ | |[[Subscriber Pricing]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates the use of a waterfall chart to visualize the components of an earnings stream from an asset.</div> | ||
+ | |[[Waterfall chart]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates how a distribution for an estimated statistic can be obtained by resampling repeatedly.</div> | ||
+ | |[[Bootstrapping]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Example of scatter plots in Analytica.</div> | ||
+ | |[[Kmeans Clustering]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates the use of Logistic and Probit regression to fit a generalized linear model to breast cancer data.</div> | ||
+ | |[[Logistic regression prior selection]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Moving Average Example]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Multidimensional Scaling]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Principle Components]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Regression Examples]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Example of how to decide where to throw a party. Shows how to model a two-branch decision tree in Analytica.</div> | ||
+ | |[[Two Branch Party Tree]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Uses the beta distribution for the Bayesian update of beliefs about the probability that a coin will come up heads.</div> | ||
+ | |[[Beta Updating]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Multi-project R&D evaluation models a typical R&D decision problem that might be faced by a biogenetic company.</div> | ||
+ | |[[Biotech R&D Portfolio]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Diversification Illustration]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Expected Value of Sampling Information (EVSI)]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Gibbs Sampling in Bayesian Network]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Models R&D decision analysis for investment strategy among several choices of powerplants for a low emissions vehicle (LEV).</div> | ||
+ | |[[LEV R&D Strategy]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates a marginal benefit/cost analysis to determine the policy alternative that leads to the most economically efficient level of cleanup.</div> | ||
+ | |[[Marginal Analysis for Control of SO2 Emissions]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Example of a multi-attribute utility analysis for cars, showing how to analyze an array of cars across an array of attributes, where different drivers assign differing weights to the importance of each attribute.</div> | ||
+ | |[[Multi-attribute Utility Analysis]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Newton-Raphson Method]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Uses decision tree terminology to provide an example asymmetric decision tree in Analytica. | ||
+ | |||
+ | </div> | ||
+ | |[[Nonsymmetric Tree]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Party With Forecast]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Plane catching decision with EVIU]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Probability of Gaussian Region (Importance Sampling)]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Calculates the required supply level to maximize profit when the profit function is asymmetric around the average demand value.</div> | ||
+ | |[[Supply and Demand]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Tornado Diagrams]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Represents a decision often faced in today’s world: which technology to purchase now, in the face of uncertain future products and prices.</div> | ||
+ | |[[Upgrade Decision]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Forecasts the population of fish and the establishment of a contagious viral disease within the population over time.</div> | ||
+ | |[[Disease establishment]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Levels staff efforts over time according to staff available, computing both the work done over time and idle time.</div> | ||
+ | |[[Leveling]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates how to simulate a Markov process using dynamic time. The example estimates the number of hospital patients over time, modeled as a Markov process.</div> | ||
+ | |[[Markov Chain]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Mass-Spring-Damper]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Models a mean-reverting price process, along with a trading strategy to "beat the market". It demonstrates the encoding of a Markov Decision Process.</div> | ||
+ | |[[Mean-reversion trading]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Minimal edit distance]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Optimal Path Dynamic Programming]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Parking Space Selection]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Projectile Motion]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Tunnel through earth]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Example of a dynamic variable that calculates growth over time, where Time is defined with unequal time steps. It is an example of exponential or linear growth or decay.</div> | ||
+ | |[[Unequal time steps]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Curve fits noisy time-sequence data using an adaptive filter.</div> | ||
+ | |[[Adaptive Filter]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Calculates the expected gain of an antenna looking at two different satellites.</div> | ||
+ | |[[Antenna Gain]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Computes the load that a Douglas-Fir Large compression post can support.</div> | ||
+ | |[[Compression Post Load Capacity]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstration showing how to analyze life cycle costs and savings from daylighting options in building design.</div> | ||
+ | |[[Daylight Analyzer]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Failure Analysis]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Ideal Gas Law]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Power dispatch]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Regular polygon calculator]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Find Words Game]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Fractals everywhere]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Probability assessment]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Abstracted Subset]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Assignment from Button]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Calculates the auto-correlation coefficients of noisy time sequence data.</div> | ||
+ | |[[Autocorrelation]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Choice and Determtables]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Correlated Distributions]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Correlated Normals]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[DBWrite Example]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Discrete Sampling]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates how to extract a diagonal from a matrix.</div> | ||
+ | |[[Extracting Diagonal]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Lookup Reindexing]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Map images from internet]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Sample Size Input Node]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Sorting People by Height]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Creates a subset array out of a larger array based on a decision criterion.</div> | ||
+ | |[[Subset of Array]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Swaps a computed or one-dimensional table value with its index, thereby making the computed value an index.</div> | ||
+ | |[[Swapping y and x-index]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Use of MDTable]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Airline NLP]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Asset allocation]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Automobile Production]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Beer Distribution LP]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Big Mac Attack]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Example of capital budgeting for four possible projects, where the objective is to decide which projects to choose in order to maximize the total return.</div> | ||
+ | |[[Capital Investment]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Diagnosing an infeasible set of linear constraints.</div> | ||
+ | |[[Infeasible]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Linear program to determine which product variants to produce and how labor should be allocated among the various production steps based on the workers’ skill sets.</div> | ||
+ | |[[Labor production allocation]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstration of a grouped-integer domain. Fill in a square with the digits 1 through n2 such that the rows and columns all sum to the same value.</div> | ||
+ | |[[Magic Square]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[NLP with Jacobian]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Optimal can dimensions]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Optimal Production Allocation]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Allocate planes to origin/destination legs to maximize gross margin.</div> | ||
+ | |[[Plane allocation LP]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">1-D example illustrating local the problem of local optima.</div> | ||
+ | |[[Polynomial NLP]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Problems with Local Optima]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Production Planning LP]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Example of a quadratically constrained optimization problem with a quadratic objective function.</div> | ||
+ | |[[Quadratic Constraints]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates how an nonlinear programming formulation can be used to solve a non- linear equation.</div> | ||
+ | |[[Solve using NLP]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Find a solution to a Sudoku puzzle.</div> | ||
+ | |[[Sudoku with Optimizer]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Find a minimal length tour through a set of cites.</div> | ||
+ | |[[Traveling salesman]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Two Mines Model]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Vacation plan with PWL tax]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Projects cost assessments of damage resulting from large earthquakes over time. It demonstrates risk analysis with time-dependence and costs of events shifted over time.</div> | ||
+ | |[[Earthquake expense risk]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Compares the value of various policies for restraints on occupants of automobiles.</div> | ||
+ | |[[Seat belt safety]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrates risk/benefit analysis, in this case regarding the benefits of reducing the emissions of fictitious air pollutant TXC.</div> | ||
+ | |[[Txc]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Rent vs Buy Model]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Rent vs Buy Analysis]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Car cost]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Car cost model ch 4]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Car cost model ch 5]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Hares sub-module - act I]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Foxes and hares sub-modules - act II]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Foxes and hares act III]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Demonstrate the building blocks for creating and editing variable definitions — expressions, standard operators, and mathematical functions.</div> | ||
+ | |[[Expression Examples]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Input and Output Nodes]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Examples in this model demonstrate the basics of working with multidimensional arrays.</div> | ||
+ | |[[Array Examples]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Examples in this model demonstrate many more of Analytica’s built-in array functions.</div> | ||
+ | |[[Array Function Examples]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Analyzing Unc & Sens]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Continuous Distributions]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Discrete Distributions]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Dynamic model that finds the downward velocity and position of a dropped object over a six second time period.</div> | ||
+ | |[[Dynamic & Dependencies]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Dynamic & Uncertainty]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Simple dynamic model, with one variable that changes over time. This example finds the gasoline price for each of five years, assuming a 5% growth rate.</div> | ||
+ | |[[Dynamic Example 1]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Slight increase in complexity over Dynamic Example 1. Instead of assuming a fixed inflation rate, this example, looks at the price with three different inflation rates for comparison. | ||
+ | |||
+ | </div> | ||
+ | |[[Dynamic Example 2]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Illustrates a dynamic loop involving simultaneous recurrences over two distinct indexes.</div> | ||
+ | |[[Dynamic on multiple indexes]] | ||
+ | |- | ||
+ | |||
+ | | Model | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Dynamic on non-Time index]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Functions that convert between binary, octal, decimal integer and hexadecimal values.</div> | ||
+ | |[[Base conversion library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Bayes Function]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Complex Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Concatenation]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Data Statistics Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Distribution Densities]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Contains various functions for defining standard distributions using different sets of parameters.</div> | ||
+ | |[[Distribution Variations]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Expand Index]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Financial Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Provides functions for writing data to and from flat files, particularly between two- dimensional tables and comma-separated value (CSV) files.</div> | ||
+ | |[[Flat File Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Garbage Bin Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Generalized Regression]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Linked List Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">Contains functions for creating several multivariate distributions.</div> | ||
+ | |[[Multivariate Distributions Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[ODBC-Library]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Optimization functions]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;">See which variables and functions are taking most of the computation time when running your model.</div> | ||
+ | |[[Performance Profiler]] | ||
+ | |- | ||
+ | |||
+ | | Library | ||
+ | |Included with software | ||
+ | | | ||
+ | | | ||
+ | |<div style="text-align: left;"></div> | ||
+ | |[[Structured Optimization Tools]] | ||
|- | |- | ||
|} | |} | ||
</div> | </div> |
Latest revision as of 16:43, 18 January 2023
This page lists example models and libraries. You can download them from here or (in some cases) link to a page with more details. Feel free to include and upload your own models and libraries.
Model/Library | Download | Domain | Methods | Description | For more |
---|---|---|---|---|---|
Model | Marginal abatement home heating.ana | carbon price, energy efficiency, climate policy | graph methods, optimal allocation, budget constraint | Shows how to set up a Marginal Abatement graph in Analytica.
|
Marginal Abatement Graph |
Model | Solar Panel Analysis.ana | renewable energy, photovoltaics, tax credits | net present value, internal rate of return, agile modeling | Explores whether it would it be cost effective to install solar panels on the roof of a house in San Jose, California.
|
Solar Panel Analysis |
Model | Items within budget.ana | Given a set of items, with a priority and a cost for each, selects out the highest priority items that fit within the fixed budget.
|
Items within Budget function | ||
Model | Grant exclusion.ana | business analysis | Tests a hypothesis about the distribution of an attribute of the marginal rejectee of a grant program, given the relevance of that attribute to award of the grant.
|
Grant Exclusion Model | |
Model | Project Priorities 5 0.ana | business models | cost analysis, net present value (NPV), uncertainty analysis | Evaluates a set of R&D projects (including uncertain R&D costs/revenues), uses multiattribute analysis to compare projects & generates the best portfolio given a R&D budget.
|
Project Planner |
Model | Steel and aluminum tariff model.ana | Estimate of the net impact of the 2018 import tariffs on steel and aluminum on the US trade deficit.
|
Steel and Aluminum import tariff impact on US trade deficit | ||
Model | Tax bracket interpolation 2021.ana | Computes amount of tax due from taxable income for a 2017 US Federal tax return.
|
Tax bracket interpolation | ||
Model | Feasible Sampler.ana | feasibility | Implements a button that will sample a collection of chance variables, then reset the sample size and keep only those sample points that are "feasible".
| ||
Model | Cross-validation example.ana | cross-validation, overfitting, non-linear kernel functions | Fits a non-linear kernel function to the residual error, and uses cross-validation to determine how many kernel functions should be used.
|
Cross-Validation / Fitting Kernel Functions to Data | |
Model | Bootstrapping.ana | bootstrapping, sampling error, re-sampling | Bootstrapping; estimates sampling error by resampling the original data.
|
Statistical Bootstrapping | |
Model | Kernel Density Estimation.ana | kernel density estimation, kernel density smoothing | Demonstrates a very simple fixed-width kernel density estimator to estimate a "smooth" probability density.
|
Smooth PDF plots using Kernel Density Estimation | |
Model | Output and input columns.ana | data analysis | Presents an input table to a user, where one column is populated with computed output data, the other column with checkboxes for the user to select.
|
Output and Input Columns in Same Table | |
Model | Platform2018b.ana | offshore platforms, oil and gas, stakeholders, rigs to reefs, decision support | decision analysis, multi-attribute, sensitivity analysis | Determined how to decommission California's 27 offshore oil platforms.
|
From Controversy to Consensus: California's offshore oil platforms |
Model | Comparing retirement account types.ana or Free 101 Compatible Version | 401(k), IRA, retirement account, decision analysis, uncertainty | MultiTables, sensitivity analysis | Explores tradeoffs between different retirement account types.
|
Retirement plan type comparison |
Model | Plane catching with UI 2020.ANA | decision theory, decision analysis, uncertainty, Monte Carlo simulation, value of information, EVPI, EVIU | Determines when you should leave home to catch an early morning plane departure.
|
Plane Catching Decision with Expected Value of Including Uncertainty | |
Model | Marginal Analysis for Control of SO2 Emissions.ana | environmental engineering | cost-benefit analysis, marginal analysis | Marginal analysis a.k.a. benefit/cost analysis to determine the policy alternative that leads us to the most economically efficient level of cleanup of acid rain from coal-burning electric-generating plants.
|
Marginal Analysis for Control of SO2 emissions |
Model | Donor-Presenter Dashboard.ana | dynamic models, Markov processes | Implements a continuous-time Markov chain in Analytica's discrete-time dynamic simulation environment. It supports immigration to, and emigration from, every node.
|
Donor/Presenter Dashboard | |
Model | Photosynthesis Regulation.ana - main regulation pathways Photosystem.ana - rough sketch of genetic regulation |
photosynthesis | dynamic models | A model of how photosynthesis is regulated inside a cyanobacteria. Simulates the concentration levels of key transport molecules along the chain.
|
Regulation of Photosynthesis |
Model | Time-series-reindexing.ana | dynamic models, forecasting, time-series re-indexing | Examples of time-series re-indexing.
|
Time-series re-indexing | |
Model | Post Compression Model | Calculator for computing the maximum load that can be handled by a Douglas Fir - Larch post of a given size, grade, and composition in a construction setting.
|
Timber Post Compression Load Capacity | ||
Model | Compression Post Load Capacity.ana | compression analysis | Computes the load that a Douglas-Fir Larch post can support in compression. Works for different timber types and grades and post sizes.
|
Compression Post Load Calculator | |
Model | Daylighting analyzer.ana | engineering | cost-benefits analysis | How to analyze lifecycle costs and savings from daylighting options in building design.
|
Daylighting Options in Building Design |
Model | California Power Plants.ana | power plants | edit table, choice menu, pulldown menu, checkbox | Example showing how to use Choice menus and Checkbox inside an Edit table.
|
California Power Plants |
Model | Requires Analytica Optimizer Electrical Transmission.ana |
electrical engineering, power generation and transmission | Electrical network model that minimizes total cost of generation and transmission.
|
Electrical Generation and Transmission | |
Model | Time of use pricing.ana & MECOLS0620.xlsx (both files needed) |
reading from spreadsheets, time-of-use pricing, electricity pricing | Time-of-use pricing is a rate tariff model used by utility companies that changes more during times when demand tends to exceed supply.
|
Time of Use pricing | |
Model | Color map.ana | computed cell formatting | A model which highlights Cell Formatting and Computed Cell Formats.
|
Color Map | |
Model | World cup.ana | Demonstrates the Poisson distribution to determine why France beat Croatia in 2018.
|
2018 World Cup Soccer final | ||
Model | resnet18.zip | residual network, deep residual learning, image recognition | Show it an image, and it tries to recognize what it is an image of, classifying it among 1000 possible categories. It uses an 18-layer residual network.
|
Image recognition | |
Model | Month to quarter.ana | aggregation, level of detail, days, weeks, months, quarters, years | Shows how to transform an array from a finer-grain index (e.g., Month) onto a coarser index (e.g., Quarter). We generally refer to this as aggregation.
|
Transforming Dimensions by transform matrix, month to quarter | |
Model | Convolution.ana | signal analysis, systems analysis | Contains several examples of convolved functions.
|
Convolution | |
Model | Dependency Tracker.ana | dependency analysis | This module tracks dependencies through your model, updating the visual appearance of nodes so that you can quickly visualize the paths by which one variable influences another.
|
Dependency Tracker Module | |
Model | French-English.ana | multi-lingual models | Maintains a single influence diagram with Title and Description attributes in both English and French.
|
Multi-lingual Influence Diagram | |
Model | Parsing XML example.ana | data extraction, xml, DOM parsing | Demonstrates two methods for extracting data: Using a full XML DOM parser, or using regular expressions.
|
Extracting Data from an XML file | |
Model | Vector Math.ana | geospatial analysis, GIS, vector analysis | Functions used for computing geospatial coordinates and distances.
|
Vector Math | |
Model | Total Allowable w Optimizer.ana or Total Allowable w StepInterp.ana for those without Optimizer |
population analysis, dynamic models, optimization analysis | Determines how many fish or animals can be caught (landed) annually so that the probability of the population declining X% in Y years (decline threshold) is less than Z% (risk tolerance).
|
Total Allowable Harvest | |
Model | Cereal Formulation1.ana | product formulation, cereal formulation | Cereal formulation/discrete mixed integer model that chooses product formulations to minimize total ingredient costs.
|
Linearizing a discrete NSP | |
Model | Neural Network.ana | feed-forward neural networks, non-linear regression | optimization analysis | Models set up to train a 2-layer feedforward sigmoid network to "learn" the concept represented by the data set(s), and then test how well it does across examples not appearing in the training set.
|
Neural Network |
Model | Earthquake expenses.ana | risk analysis, cost analysis | An example of risk analysis with time-dependence and costs shifted over time.
|
Earthquake Expenses | |
Model | Best used with Analytica Optimizer Loan policy selection.ana |
creditworthiness, credit rating, default risk | risk analysis | Helps a lender decide optimal credit rating threshold to require and what interest rate (above prime) to charge.
|
Loan Policy Selection |
Model | Hubbard_and_Seiersen_cyberrisk.ana | cybersecurity risk | loss exceedance curve, simulation | Simulates loss exceedance curves for a set of cybersecurity events, the likelihood and probabilistic monetary impact of which have been characterized by system experts.
|
Inherent and Residual Risk Simulation |
Model | Media:Red_State_Blue_State_plot.ana | map, states | graphing | Example containing the shape outlines for each of the 50 US states, along with a graph that uses color to depict something that varies by state.
|
Red or blue state |
Model | COVID Model 2020--03-25.ana | covid, covid-19, coronavirus, corona, epidemic | A systems dynamics style SICR model of the COVID-19 outbreak within the state of Colorado.
|
COVID-19 State Simulator, a Systems Dynamics approach | |
Model | Corona Markov.ana | covid, covid-19, coronavirus, corona, epidemic, sensitivity analyses | Explores the progression of the COVID-19 coronavirus epidemic in the US, and to explore the effects of different levels of social isolation.
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How social isolation impacts COVID-19 spread in the US - A Markov model approach | |
Model | Modelo Epidemiológoco para el Covid-19 con cuarentena.ana | covid, covid-19, coronavirus, corona, epidemic | Un modelo en cadena de Markov del impacto previsto de la enfermedad coronavirus COVID-19 en el Perú, y del impacto del aislamiento social.
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Epidemiological model of COVID-19 for Perú, en español | |
Model | COVID-19 Triangle Suppression.ana | covid, covid-19, coronavirus, corona, epidemic | Models progression of the COVID-19 pandemic in the US, understanding the amount of time that is required for lock down measures when a suppression strategy is adopted.
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A Triangle Suppression model of COVID-19 | |
Model | Simple COVID-19.ana | covid, covid-19, coronavirus, corona, epidemic | Explores possible COVID-19 Coronavirus scenarios from the beginning of March, 2020 through the end of 2020 in the US.
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COVID-19 Coronavirus SICR progression for 2020 | |
Model | US COVID-19 Data.ana | covid, covid-19, coronavirus, corona, epidemic, death, infection | Reads in COVID-19 data from the New York Times and transforms it into a form that is convenient to work with in Analytica.
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COVID-19 Case and Death data for US states and counties | |
Model | Voluntary vs mandatory testing.ana | covid, covid-19, coronavirus, corona, epidemic | Computes the rate of infection in scenarios when COVID-19 testing is required/optional,based on prevalence rates, test accuracies and voluntary testing rates.
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Mandatory vs Voluntary testing policies | |
Model | Included with software | Takes typical bond purchase inputs (purchase price, par value, interest rate, and life to maturity) and calculates bond cash flows, current yield, and yield to maturity.
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Bond Model | ||
Model | Included with software | Example of a breakeven analysis of a set of revenue levels, when the fixed expenses are set at one amount and the variable expenses are a constant fraction of revenue.
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Breakeven Analysis | ||
Model | Included with software | Evaluates and compares the expected commercialization value of multiple proposed R&D projects.
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Expected R&D Project Value | ||
Model | Included with software | Financial Statement Templates | |||
Model | Included with software | Explores a market for a new product, and the pricing and advertising budget decisions involved.
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Market Model | ||
Model | Included with software | Takes input data for activity paths required to complete a project, and calculates various outputs describing the critical path, timing, and costs for project completion.
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Plan_Schedule_ Control | ||
Model | Included with software | Evaluates and prioritizes a portfolio of projects based on either the estimated net present value or a multi-attribute score, based on strategy fit, staff development, the generation of public goodwill, and estimated net revenue.
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Project Portfolio Planner | ||
Model | Included with software | Sales Effectiveness | |||
Model | Included with software | Subscriber Pricing | |||
Model | Included with software | Demonstrates the use of a waterfall chart to visualize the components of an earnings stream from an asset.
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Waterfall chart | ||
Model | Included with software | Demonstrates how a distribution for an estimated statistic can be obtained by resampling repeatedly.
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Bootstrapping | ||
Model | Included with software | Example of scatter plots in Analytica.
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Kmeans Clustering | ||
Model | Included with software | Demonstrates the use of Logistic and Probit regression to fit a generalized linear model to breast cancer data.
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Logistic regression prior selection | ||
Model | Included with software | Moving Average Example | |||
Model | Included with software | Multidimensional Scaling | |||
Model | Included with software | Principle Components | |||
Model | Included with software | Regression Examples | |||
Model | Included with software | Example of how to decide where to throw a party. Shows how to model a two-branch decision tree in Analytica.
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Two Branch Party Tree | ||
Model | Included with software | Uses the beta distribution for the Bayesian update of beliefs about the probability that a coin will come up heads.
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Beta Updating | ||
Model | Included with software | Multi-project R&D evaluation models a typical R&D decision problem that might be faced by a biogenetic company.
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Biotech R&D Portfolio | ||
Model | Included with software | Diversification Illustration | |||
Model | Included with software | Expected Value of Sampling Information (EVSI) | |||
Model | Included with software | Gibbs Sampling in Bayesian Network | |||
Model | Included with software | Models R&D decision analysis for investment strategy among several choices of powerplants for a low emissions vehicle (LEV).
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LEV R&D Strategy | ||
Model | Included with software | Demonstrates a marginal benefit/cost analysis to determine the policy alternative that leads to the most economically efficient level of cleanup.
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Marginal Analysis for Control of SO2 Emissions | ||
Model | Included with software | Example of a multi-attribute utility analysis for cars, showing how to analyze an array of cars across an array of attributes, where different drivers assign differing weights to the importance of each attribute.
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Multi-attribute Utility Analysis | ||
Model | Included with software | Newton-Raphson Method | |||
Model | Included with software | Uses decision tree terminology to provide an example asymmetric decision tree in Analytica.
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Nonsymmetric Tree | ||
Model | Included with software | Party With Forecast | |||
Model | Included with software | Plane catching decision with EVIU | |||
Model | Included with software | Probability of Gaussian Region (Importance Sampling) | |||
Model | Included with software | Calculates the required supply level to maximize profit when the profit function is asymmetric around the average demand value.
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Supply and Demand | ||
Model | Included with software | Tornado Diagrams | |||
Model | Included with software | Represents a decision often faced in today’s world: which technology to purchase now, in the face of uncertain future products and prices.
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Upgrade Decision | ||
Model | Included with software | Forecasts the population of fish and the establishment of a contagious viral disease within the population over time.
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Disease establishment | ||
Model | Included with software | Levels staff efforts over time according to staff available, computing both the work done over time and idle time.
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Leveling | ||
Model | Included with software | Demonstrates how to simulate a Markov process using dynamic time. The example estimates the number of hospital patients over time, modeled as a Markov process.
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Markov Chain | ||
Model | Included with software | Mass-Spring-Damper | |||
Model | Included with software | Models a mean-reverting price process, along with a trading strategy to "beat the market". It demonstrates the encoding of a Markov Decision Process.
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Mean-reversion trading | ||
Model | Included with software | Minimal edit distance | |||
Model | Included with software | Optimal Path Dynamic Programming | |||
Model | Included with software | Parking Space Selection | |||
Model | Included with software | Projectile Motion | |||
Model | Included with software | Tunnel through earth | |||
Model | Included with software | Example of a dynamic variable that calculates growth over time, where Time is defined with unequal time steps. It is an example of exponential or linear growth or decay.
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Unequal time steps | ||
Model | Included with software | Curve fits noisy time-sequence data using an adaptive filter.
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Adaptive Filter | ||
Model | Included with software | Calculates the expected gain of an antenna looking at two different satellites.
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Antenna Gain | ||
Model | Included with software | Computes the load that a Douglas-Fir Large compression post can support.
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Compression Post Load Capacity | ||
Model | Included with software | Demonstration showing how to analyze life cycle costs and savings from daylighting options in building design.
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Daylight Analyzer | ||
Model | Included with software | Failure Analysis | |||
Model | Included with software | Ideal Gas Law | |||
Model | Included with software | Power dispatch | |||
Model | Included with software | Regular polygon calculator | |||
Model | Included with software | Find Words Game | |||
Model | Included with software | Fractals everywhere | |||
Model | Included with software | Probability assessment | |||
Model | Included with software | Abstracted Subset | |||
Model | Included with software | Assignment from Button | |||
Model | Included with software | Calculates the auto-correlation coefficients of noisy time sequence data.
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Autocorrelation | ||
Model | Included with software | Choice and Determtables | |||
Model | Included with software | Correlated Distributions | |||
Model | Included with software | Correlated Normals | |||
Model | Included with software | DBWrite Example | |||
Model | Included with software | Discrete Sampling | |||
Model | Included with software | Demonstrates how to extract a diagonal from a matrix.
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Extracting Diagonal | ||
Model | Included with software | Lookup Reindexing | |||
Model | Included with software | Map images from internet | |||
Model | Included with software | Sample Size Input Node | |||
Model | Included with software | Sorting People by Height | |||
Model | Included with software | Creates a subset array out of a larger array based on a decision criterion.
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Subset of Array | ||
Model | Included with software | Swaps a computed or one-dimensional table value with its index, thereby making the computed value an index.
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Swapping y and x-index | ||
Model | Included with software | Use of MDTable | |||
Model | Included with software | Airline NLP | |||
Model | Included with software | Asset allocation | |||
Model | Included with software | Automobile Production | |||
Model | Included with software | Beer Distribution LP | |||
Model | Included with software | Big Mac Attack | |||
Model | Included with software | Example of capital budgeting for four possible projects, where the objective is to decide which projects to choose in order to maximize the total return.
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Capital Investment | ||
Model | Included with software | Diagnosing an infeasible set of linear constraints.
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Infeasible | ||
Model | Included with software | Linear program to determine which product variants to produce and how labor should be allocated among the various production steps based on the workers’ skill sets.
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Labor production allocation | ||
Model | Included with software | Demonstration of a grouped-integer domain. Fill in a square with the digits 1 through n2 such that the rows and columns all sum to the same value.
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Magic Square | ||
Model | Included with software | NLP with Jacobian | |||
Model | Included with software | Optimal can dimensions | |||
Model | Included with software | Optimal Production Allocation | |||
Model | Included with software | Allocate planes to origin/destination legs to maximize gross margin.
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Plane allocation LP | ||
Model | Included with software | 1-D example illustrating local the problem of local optima.
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Polynomial NLP | ||
Model | Included with software | Problems with Local Optima | |||
Model | Included with software | Production Planning LP | |||
Model | Included with software | Example of a quadratically constrained optimization problem with a quadratic objective function.
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Quadratic Constraints | ||
Model | Included with software | Demonstrates how an nonlinear programming formulation can be used to solve a non- linear equation.
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Solve using NLP | ||
Model | Included with software | Find a solution to a Sudoku puzzle.
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Sudoku with Optimizer | ||
Model | Included with software | Find a minimal length tour through a set of cites.
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Traveling salesman | ||
Model | Included with software | Two Mines Model | |||
Model | Included with software | Vacation plan with PWL tax | |||
Model | Included with software | Projects cost assessments of damage resulting from large earthquakes over time. It demonstrates risk analysis with time-dependence and costs of events shifted over time.
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Earthquake expense risk | ||
Model | Included with software | Compares the value of various policies for restraints on occupants of automobiles.
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Seat belt safety | ||
Model | Included with software | Demonstrates risk/benefit analysis, in this case regarding the benefits of reducing the emissions of fictitious air pollutant TXC.
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Txc | ||
Model | Included with software | Rent vs Buy Model | |||
Model | Included with software | Rent vs Buy Analysis | |||
Model | Included with software | Car cost | |||
Model | Included with software | Car cost model ch 4 | |||
Model | Included with software | Car cost model ch 5 | |||
Model | Included with software | Hares sub-module - act I | |||
Model | Included with software | Foxes and hares sub-modules - act II | |||
Model | Included with software | Foxes and hares act III | |||
Model | Included with software | Demonstrate the building blocks for creating and editing variable definitions — expressions, standard operators, and mathematical functions.
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Expression Examples | ||
Model | Included with software | Input and Output Nodes | |||
Model | Included with software | Examples in this model demonstrate the basics of working with multidimensional arrays.
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Array Examples | ||
Model | Included with software | Examples in this model demonstrate many more of Analytica’s built-in array functions.
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Array Function Examples | ||
Model | Included with software | Analyzing Unc & Sens | |||
Model | Included with software | Continuous Distributions | |||
Model | Included with software | Discrete Distributions | |||
Model | Included with software | Dynamic model that finds the downward velocity and position of a dropped object over a six second time period.
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Dynamic & Dependencies | ||
Model | Included with software | Dynamic & Uncertainty | |||
Model | Included with software | Simple dynamic model, with one variable that changes over time. This example finds the gasoline price for each of five years, assuming a 5% growth rate.
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Dynamic Example 1 | ||
Model | Included with software | Slight increase in complexity over Dynamic Example 1. Instead of assuming a fixed inflation rate, this example, looks at the price with three different inflation rates for comparison.
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Dynamic Example 2 | ||
Model | Included with software | Illustrates a dynamic loop involving simultaneous recurrences over two distinct indexes.
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Dynamic on multiple indexes | ||
Model | Included with software | Dynamic on non-Time index | |||
Library | Included with software | Functions that convert between binary, octal, decimal integer and hexadecimal values.
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Base conversion library | ||
Library | Included with software | Bayes Function | |||
Library | Included with software | Complex Library | |||
Library | Included with software | Concatenation | |||
Library | Included with software | Data Statistics Library | |||
Library | Included with software | Distribution Densities | |||
Library | Included with software | Contains various functions for defining standard distributions using different sets of parameters.
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Distribution Variations | ||
Library | Included with software | Expand Index | |||
Library | Included with software | Financial Library | |||
Library | Included with software | Provides functions for writing data to and from flat files, particularly between two- dimensional tables and comma-separated value (CSV) files.
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Flat File Library | ||
Library | Included with software | Garbage Bin Library | |||
Library | Included with software | Generalized Regression | |||
Library | Included with software | Linked List Library | |||
Library | Included with software | Contains functions for creating several multivariate distributions.
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Multivariate Distributions Library | ||
Library | Included with software | ODBC-Library | |||
Library | Included with software | Optimization functions | |||
Library | Included with software | See which variables and functions are taking most of the computation time when running your model.
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Performance Profiler | ||
Library | Included with software | Structured Optimization Tools |
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