Example Models
The Wiki pages here provide a repository for Analytica models and libraries. Supplementary material may be included here describing the model, its usage, etc. Models or libraries may be contributed because they are useful for particular applications, provide a starting point for certain modeling tasks, demonstrate an Analytica concept, etc.
Several dozen models are included with the Analytica distribution, installed onto your machine when you install Analytica. These models are not also here on the Wiki yet, but may be added in the future. Furthermore, as updates to these models occur, more recent versions will be made available here.
Analytica users may also contribute their own models and examples here. For instructions on how to upload your own contributions, see Uploading Example Models.
Grant Exclusion Model
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.
Donor/Presenter Dashboard
This model implements a continuous-time Markov chain in Analytica's discrete-time dynamic simulation environment. It supports immigration to, and emigration from, every node.
It can be used by an arts organization to probabilistically forecast future audience evolution, in both the short and the long (steady state) term. It also allows for uncertainty in the input parameters.
Project Planner
Download: Project Priorities 5 0.ana
A demo model that shows how to:
- Evaluate a set of R&D projects, including uncertain R&D costs, and uncertain revenues if it leads to release of a commercial product.
- Use multiattribute analysis to compare projects, including a hard attribute -- expected net present value -- and soft attributes -- strategic fit, staff development, and public good will.
- Compare cost, NPV, and multiattribute value for a selected portfolio of projects.
- Generate the best portfolio (ratio of NPV or multiattribute merit to cost) given a R&D budget.
This link is only a test, and to an older version: <link target="blank">http://lumina.com/wiki/images/4/43/Project_priorities_2007_4.0.ANA</link>
California Power Plants
A model that demonstrates the use of choice pulldowns in edit tables. The model is created during a mini-tutorial on Inserting_Choice_Controls_in_Edit_Table_Cells elsewhere on this Wiki.
Media:California_Power_Plants.ANA
Dependency Tracker Module
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. You can also use it to provide a visual indication of which nodes are downstream (or upstream) from an indicated variable.
The module contains button scripts that change the bevel appearance of nodes in your model. To see how Variable X influences Variable Y, the script will bevel the nodes for all variables that are influenced by X and influence Y. Alternatively, you can bevel all nodes that are influenced by X, or you can bevel all nodes that influence Y.
In the image above, the path from dp_ex_2 through dp_ex_4 has been highlight using the bevel style of the nodes. (The result of pressing the "Bevel all from Ancestor to Descendant" button)
Total Allowable Harvest from a population of uncertain size, growth rate, in a fishery of uncertain
The problem applies to any population of fish or animal whose dynamics are poorly known but can be summarized in a simple model:
N_t+1 = Nt*Lambda - landed catch*(1+loss rate).
The question here is to determine how many fish or animal can be caught (landed) annually so that the probability of the population declining X% in Y years (decline threshold) is less than Y% (risk tolerance). For example, in the example models given:
P( 10% decline in 10 years) <= 10%
Two models are available for download. One uses the Optimizer (NlpDefine) to find the maximum landed catch that . The other (for those using a version of Analytica without Optimizer) uses StepInterp in an iterative way to get the maximum landed catch.
Models were contributed by Pierre Richard, Department of Fisheries and Oceans Canada, Winnipeg
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