1. Model Estimation
(New to version 0.88)
In addition to parameter estimation (see ParamEst), one may use an algorithm to systematically alter a model in order to achieve a fit of its performance to given criteria. This may be called model estimation, a.k.a. model inference.
To support this, a number of tools are provided for manipulating model descriptions (using ModelSpec), via a class of model Transforms.
One may also take advantage of a library (class ModelLibrary) of model description primitives, from which to base a systematic search of a "model space" suitable to the model estimation problem.
A ModelManager instance is a repository for all models related by a class of transformations. In order to build model instantiations that are ready to simulate, the GDescriptor and MDescriptor classes are used to hold all the specific details of how to instantiate a model once it is mathematically specified. Upon demand, these are then fed by the model manager into a ModelConstructor object to build a new model. The model manager is also the access point for creating transformations of a model into another.