Difference between revisions of "Example Models and Libraries - Table"
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− | |[[]] | + | |[[Expected R&D Project Value]] |
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− | |[[]] | + | |[[Financial Statement Templates]] |
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− | |[[]] | + | |[[Market Model]] |
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− | |[[]] | + | |[[Plan_Schedule_ Control]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Project Portfolio Planner]] |
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− | |[[]] | + | |[[Sales Effectiveness]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Subscriber Pricing]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Waterfall chart]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Bootstrapping]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Kmeans Clustering]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Logistic regression prior selection]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Moving Average Example]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Multidimensional Scaling]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Principle Components]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Regression Examples]] |
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− | |[[]] | + | |[[Two Branch Party Tree]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Beta Updating]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Biotech R&D Portfolio]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Diversification Illustration]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Expected Value of Sampling Information (EVSI)]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Gibbs Sampling in Bayesian Network]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[LEV R&D Strategy]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Marginal Analysis for Control of SO2 Emissions]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Multi-attribute Utility Analysis]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Newton-Raphson Method]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Nonsymmetric Tree]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Party With Forecast]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Plane catching decision with EVIU]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Probability of Gaussian Region (Importance Sampling)]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Supply and Demand]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Tornado Diagrams]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Upgrade Decision]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Disease establishment]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Leveling]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Markov Chain]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Mass-Spring-Damper]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Mean-reversion trading]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Minimal edit distance]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Optimal Path Dynamic Programming]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Parking Space Selection]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Projectile Motion]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Tunnel through earth]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Unequal time steps]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Curve fits noisy time-sequence data using an adaptive filter.</div> |
− | |[[]] | + | |[[Adaptive Filter]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Calculates the expected gain of an antenna looking at two different satellites.</div> |
− | |[[]] | + | |[[Antenna Gain]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Computes the load that a Douglas-Fir Large compression post can support.</div> |
− | |[[]] | + | |[[Compression Post Load Capacity]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Demonstration showing how to analyze life cycle costs and savings from daylighting options in building design.</div> |
− | |[[]] | + | |[[Daylight Analyzer]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Failure Analysis]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Ideal Gas Law]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Power dispatch]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Regular polygon calculator]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Find Words Game]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Fractals everywhere]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Probability assessment]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Abstracted Subset]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Assignment from Button]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Calculates the auto-correlation coefficients of noisy time sequence data.</div> |
− | |[[]] | + | |[[Autocorrelation]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Choice and Determtables]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Correlated Distributions]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Correlated Normals]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[DBWrite Example]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Discrete Sampling]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Demonstrates how to extract a diagonal from a matrix.</div> |
− | |[[]] | + | |[[Extracting Diagonal]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Lookup Reindexing]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Map images from internet]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Sample Size Input Node]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Sorting People by Height]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Creates a subset array out of a larger array based on a decision criterion.</div> |
− | |[[]] | + | |[[Subset of Array]] |
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− | |<div style="text-align: left;"></div> | + | |<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]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Use of MDTable]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Airline NLP]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Asset allocation]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Automobile Production]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Beer Distribution LP]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Big Mac Attack]] |
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− | |<div style="text-align: left;"></div> | + | |<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]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Diagnosing an infeasible set of linear constraints.</div> |
− | |[[]] | + | |[[Infeasible]] |
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− | |<div style="text-align: left;"></div> | + | |<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]] |
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− | |<div style="text-align: left;"></div> | + | |<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]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[NLP with Jacobian]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Optimal can dimensions]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Optimal Production Allocation]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Allocate planes to origin/destination legs to maximize gross margin.</div> |
− | |[[]] | + | |[[Plane allocation LP]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">1-D example illustrating local the problem of local optima.</div> |
− | |[[]] | + | |[[Polynomial NLP]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Problems with Local Optima]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Production Planning LP]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Example of a quadratically constrained optimization problem with a quadratic objective function.</div> |
− | |[[]] | + | |[[Quadratic Constraints]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Demonstrates how an nonlinear programming formulation can be used to solve a non- linear equation.</div> |
− | |[[]] | + | |[[Solve using NLP]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Find a solution to a Sudoku puzzle.</div> |
− | |[[]] | + | |[[Sudoku with Optimizer]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Find a minimal length tour through a set of cites.</div> |
− | |[[]] | + | |[[Traveling salesman]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Two Mines Model]] |
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|<div style="text-align: left;"></div> | |<div style="text-align: left;"></div> | ||
− | |[[]] | + | |[[Vacation plan with PWL tax]] |
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− | |<div style="text-align: left;"></div> | + | |<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]] |
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− | |<div style="text-align: left;"></div> | + | |<div style="text-align: left;">Compares the value of various policies for restraints on occupants of automobiles.</div> |
− | |[[]] | + | |[[Seat belt safety]] |
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− | |<div style="text-align: left;"></div> | + | |<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]] |
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Revision as of 16:13, 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 |
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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".
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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.
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Cross-Validation / Fitting Kernel Functions to Data | |
Model | Bootstrapping.ana | bootstrapping, sampling error, re-sampling | Bootstrapping; estimates sampling error by resampling the original data.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Regulation of Photosynthesis |
Model | Time-series-reindexing.ana | dynamic models, forecasting, time-series re-indexing | Examples of time-series re-indexing.
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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.
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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.
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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.
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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.
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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.
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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.
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Time of Use pricing | |
Model | Color map.ana | computed cell formatting | A model which highlights Cell Formatting and Computed Cell Formats.
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Color Map | |
Model | World cup.ana | Demonstrates the Poisson distribution to determine why France beat Croatia in 2018.
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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.
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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.
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Transforming Dimensions by transform matrix, month to quarter | |
Model | Convolution.ana | signal analysis, systems analysis | Contains several examples of convolved functions.
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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.
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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.
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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.
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Extracting Data from an XML file | |
Model | Vector Math.ana | geospatial analysis, GIS, vector analysis | Functions used for computing geospatial coordinates and distances.
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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).
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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.
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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.
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Neural Network |
Model | Earthquake expenses.ana | risk analysis, cost analysis | An example of risk analysis with time-dependence and costs shifted over time.
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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.
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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.
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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.
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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.
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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 | |
Library | Included with software | Bond Model | |||
Library | Included with software | Breakeven Analysis | |||
Library | Included with software | Expected R&D Project Value | |||
Library | Included with software | Financial Statement Templates | |||
Library | Included with software | Market Model | |||
Library | Included with software | Plan_Schedule_ Control | |||
Library | Included with software | Project Portfolio Planner | |||
Library | Included with software | Sales Effectiveness | |||
Library | Included with software | Subscriber Pricing | |||
Library | Included with software | Waterfall chart | |||
Library | Included with software | Bootstrapping | |||
Library | Included with software | Kmeans Clustering | |||
Library | Included with software | Logistic regression prior selection | |||
Library | Included with software | Moving Average Example | |||
Library | Included with software | Multidimensional Scaling | |||
Library | Included with software | Principle Components | |||
Library | Included with software | Regression Examples | |||
Library | Included with software | Two Branch Party Tree | |||
Library | Included with software | Beta Updating | |||
Library | Included with software | Biotech R&D Portfolio | |||
Library | Included with software | Diversification Illustration | |||
Library | Included with software | Expected Value of Sampling Information (EVSI) | |||
Library | Included with software | Gibbs Sampling in Bayesian Network | |||
Library | Included with software | LEV R&D Strategy | |||
Library | Included with software | Marginal Analysis for Control of SO2 Emissions | |||
Library | Included with software | Multi-attribute Utility Analysis | |||
Library | Included with software | Newton-Raphson Method | |||
Library | Included with software | Nonsymmetric Tree | |||
Library | Included with software | Party With Forecast | |||
Library | Included with software | Plane catching decision with EVIU | |||
Library | Included with software | Probability of Gaussian Region (Importance Sampling) | |||
Library | Included with software | Supply and Demand | |||
Library | Included with software | Tornado Diagrams | |||
Library | Included with software | Upgrade Decision | |||
Library | Included with software | Disease establishment | |||
Library | Included with software | Leveling | |||
Library | Included with software | Markov Chain | |||
Library | Included with software | Mass-Spring-Damper | |||
Library | Included with software | Mean-reversion trading | |||
Library | Included with software | Minimal edit distance | |||
Library | Included with software | Optimal Path Dynamic Programming | |||
Library | Included with software | Parking Space Selection | |||
Library | Included with software | Projectile Motion | |||
Library | Included with software | Tunnel through earth | |||
Library | Included with software | Unequal time steps | |||
Library | Included with software | Curve fits noisy time-sequence data using an adaptive filter.
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Adaptive Filter | ||
Library | Included with software | Calculates the expected gain of an antenna looking at two different satellites.
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Antenna Gain | ||
Library | Included with software | Computes the load that a Douglas-Fir Large compression post can support.
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Compression Post Load Capacity | ||
Library | 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 | ||
Library | Included with software | Failure Analysis | |||
Library | Included with software | Ideal Gas Law | |||
Library | Included with software | Power dispatch | |||
Library | Included with software | Regular polygon calculator | |||
Library | Included with software | Find Words Game | |||
Library | Included with software | Fractals everywhere | |||
Library | Included with software | Probability assessment | |||
Library | Included with software | Abstracted Subset | |||
Library | Included with software | Assignment from Button | |||
Library | Included with software | Calculates the auto-correlation coefficients of noisy time sequence data.
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Autocorrelation | ||
Library | Included with software | Choice and Determtables | |||
Library | Included with software | Correlated Distributions | |||
Library | Included with software | Correlated Normals | |||
Library | Included with software | DBWrite Example | |||
Library | Included with software | Discrete Sampling | |||
Library | Included with software | Demonstrates how to extract a diagonal from a matrix.
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Extracting Diagonal | ||
Library | Included with software | Lookup Reindexing | |||
Library | Included with software | Map images from internet | |||
Library | Included with software | Sample Size Input Node | |||
Library | Included with software | Sorting People by Height | |||
Library | Included with software | Creates a subset array out of a larger array based on a decision criterion.
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Subset of Array | ||
Library | 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 | ||
Library | Included with software | Use of MDTable | |||
Library | Included with software | Airline NLP | |||
Library | Included with software | Asset allocation | |||
Library | Included with software | Automobile Production | |||
Library | Included with software | Beer Distribution LP | |||
Library | Included with software | Big Mac Attack | |||
Library | 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 | ||
Library | Included with software | Diagnosing an infeasible set of linear constraints.
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Infeasible | ||
Library | 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 | ||
Library | 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 | ||
Library | Included with software | NLP with Jacobian | |||
Library | Included with software | Optimal can dimensions | |||
Library | Included with software | Optimal Production Allocation | |||
Library | Included with software | Allocate planes to origin/destination legs to maximize gross margin.
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Plane allocation LP | ||
Library | Included with software | 1-D example illustrating local the problem of local optima.
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Polynomial NLP | ||
Library | Included with software | Problems with Local Optima | |||
Library | Included with software | Production Planning LP | |||
Library | Included with software | Example of a quadratically constrained optimization problem with a quadratic objective function.
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Quadratic Constraints | ||
Library | 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 | ||
Library | Included with software | Find a solution to a Sudoku puzzle.
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Sudoku with Optimizer | ||
Library | Included with software | Find a minimal length tour through a set of cites.
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Traveling salesman | ||
Library | Included with software | Two Mines Model | |||
Library | Included with software | Vacation plan with PWL tax | |||
Library | 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 | ||
Library | Included with software | Compares the value of various policies for restraints on occupants of automobiles.
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Seat belt safety | ||
Library | 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 | ||
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