Example Models - Table
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.
Download Model | Domain | Description | Methods | For more |
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Marginal abatement home heating.ana | carbon price, energy efficiency, climate policy | This model, along with the accompanying blog article, show how to set up a Marginal Abatement graph in Analytica. | graph methods, optimal allocation, budget constraint | Marginal Abatement Graph |
Solar Panel Analysis.ana | renewable energy, photovoltaics, tax credits | Would it be cost effective to install solar panels on the roof of my house? This model explores this question for my situation in San Jose, California. An accompanying video documents the building of this model, and is a good example of the process one goes through when building any decision model.
The model explores how many panels I should install, and what the payoff is in terms of net present value, Internal rate of return and time to recoup cost. It also looks at whether I should postpone the start of the installation to take advantage of rapidly falling PV prices, or cash in on tax credits. |
net present value, internal rate of return, agile modeling | Solar Panel Analysis |
Items within budget.ana | Given a set of items, with a priority and a cost for each, the function Items_within_budget function selects out the highest priority items that fit within the fixed budget. | Items within Budget function | ||
Grant exclusion.ana | business analysis | This model 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. It could be used by an organization to make decisions as to whether to fiscally-sponsor another organization that will use that fiscal sponsorship to apply for grants, by looking at the effect on the pool of grant recipients overall. | Grant Exclusion Model | |
Project Priorities 5 0.ana | business models | This is a demo model that shows how to:
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cost analysis, net present value (NPV), uncertainty analysis | Project Planner |
Steel and aluminum tariff model.ana | On 2-March-2018, President Trump proposed new import tariffs on steel and aluminum. It seems as if the projected net impacts of these tariffs on the total US trade deficit and US economy depends largely on which news outlets you get your news from. We thought it would be helpful to put together a simple and easy to understand model to estimate of the net impact of these tariffs on the US trade deficit, assuming that no other factors change (e.g., no retaliatory tariffs are enacted by other countries). We wanted something that allows you to understand how its estimates are being derived, with assumptions that can be easily replaced with your own, so that the model itself would be impartial to any particular viewpoint. We want the uncertainties that are inherent in such a simple model to be explicit, so you can see the range of possibilities and not just a single guess. Finally, we wanted the model to be easy to understand fully for non-economists (a group to which we belong, too).
This model accompanied a current event blog post on the Lumina blog: Impact of Trump’s proposed Steel & Aluminum tariffs on US trade deficit |
Steel and Aluminum import tariff impact on US trade deficit | ||
Tax bracket interpolation 2021.ana | Computes amount of tax due from taxable income for a 2017 US Federal tax return. To match the IRS's numbers exactly, it is necessary to process tax brackets correctly as well as implementation a complex mix of rounding rules that reproduce the 12 pages of table lookups from the Form 1040 instructions. This model is showcased in a blog article, How to simplify the IRS Tax Tables. | Tax bracket interpolation | ||
Feasible Sampler.ana | feasibility | You have a bunch of chance variables, each with a probability distribution. Their joint sample, however, contains some combinations of points that are (for one reason or another) physically impossible. We'll call those infeasible points. You'd like to eliminate those points from the sample and keep only the feasible points.
This module 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". Obviously, this approach will work best when most of your samples are feasible. If you can handle the "infeasible" points in your model directly, by conditioning certain chance variables on others, that is far preferable. But there are some cases where this solution (although a bit of a kludge) is more convenient. The instructions for how to use this are in the module description field. |
statistics, sampling, importance sampling, Monte Carlo simulation | Sampling from only feasible points |
Cross-validation example.ana | When fitting a function to data, if you have too many free parameters relative to the number of points in your data set, you may "overfit" the data. When this happens, the fit to your training data may be very good, but the fit to new data points (beyond those used for training) may be very poor.
Cross-validation is a common technique to deal with this problem: We set aside a fraction of the available data as a cross-validation set. Then we begin by fitting very simple functions to the data (with few free parameters), successively increasing the number of free parameters, and seeing how the predictive performance changes on the cross-validation set. It is typical to see improvement on the cross-validation set for a while, followed by a deterioration of predictive performance on the cross-validation set once overfitting starts occurring. This example model successively fits a non-linear kernel function to the residual error, and uses cross-validation to determine how many kernel functions should be used. Requires Analytica Optimizer: The kernel fitting function (Kern_Fit) uses NlpDefine. |
Cross-Validation / Fitting Kernel Functions to Data | ||
Bootstrapping.ana | Statistical Bootstrapping | |||
Kernel Density Estimation.ana | Smooth PDF plots using Kernel Density Estimation | |||
Output and input columns.ana | Output and Input Columns in Same Table | |||
Platform2018b.ana | From Controversy to Consensus: California's offshore oil platforms | |||
Comparing retirement account types.ana or Free 101 Compatible Version | Retirement plan type comparison | |||
Plane catching with UI 2020.ANA | Plane Catching Decision with Expected Value of Including Uncertainty | |||
Marginal Analysis for Control of SO2 Emissions.ana | Marginal Analysis for Control of SO2 emissions | |||
Donor-Presenter Dashboard.ana | Donor/Presenter Dashboard | |||
Photosynthesis Regulation.ana - main regulation pathways Photosystem.ana - rough sketch of genetic regulation |
Regulation of Photosynthesis | |||
Time-series-reindexing.ana | Time-series re-indexing | |||
Post Compression Model | Timber Post Compression Load Capacity | |||
Compression Post Load Capacity.ana | Compression Post Load Calculator | |||
Daylighting analyzer.ana | Daylighting Options in Building Design | |||
California Power Plants.ana | California Power Plants | |||
Electrical Transmission.ana | Electrical Generation and Transmission | |||
Time of use pricing.ana & MECOLS0620.xlsx (both files needed) |
Time of Use pricing | |||
Color map.ana | Color Map | |||
World cup.ana | 2018 World Cup Soccer final | |||
resnet18.zip | Image recognition | |||
Month to quarter.ana | Transforming Dimensions by transform matrix, month to quarter | |||
Convolution.ana | Convolution | |||
Dependency Tracker.ana | Dependency Tracker Module | |||
French-English.ana | Multi-lingual Influence Diagram | |||
Parsing XML example.ana | Extracting Data from an XML file | |||
Vector Math.ana | Vector Math | |||
Total Allowable w Optimizer.ana or Total Allowable w StepInterp.ana for those without Optimizer |
Total Allowable Harvest | |||
Cereal Formulation1.ana | Linearizing a discrete NSP | |||
Neural Network.ana | Neural Network | |||
Earthquake expenses.ana | Earthquake Expenses | |||
Loan policy selection.ana | Loan Policy Selection | |||
Hubbard_and_Seiersen_cyberrisk.ana | Inherent and Residual Risk Simulation | |||
media:Red State Blue State plot.ana | Red or blue state | |||
COVID Model 2020--03-25.ana | COVID-19 State Simulator, a Systems Dynamics approach | |||
Corona Markov.ana | How social isolation impacts COVID-19 spread in the US - A Markov model approach | |||
Modelo Epidemiológoco para el Covid-19 con cuarentena.ana | Epidemiological model of COVID-19 for Perú, en español | |||
COVID-19 Triangle Suppression.ana | A Triangle Suppression model of COVID-19 | |||
Simple COVID-19.ana | COVID-19 Coronavirus SICR progression for 2020 | |||
US COVID-19 Data.ana | COVID-19 Case and Death data for US states and counties | |||
Voluntary vs mandatory testing.ana | Mandatory vs Voluntary testing policies |
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