StateSpaceInference sub-classes are specific to a particular density (i.e. GaussianInference, StudentInference). That is, sub-classes are designed with the Bayesian viewpoint, which imposes density on the joint p(x, z). But the same philosophy isn't followed for moment transforms!
For reasons of consistency, the same Bayesian philosophy should be reflected in the class hierarchy of the "moment" transforms (they should really be referred to as statistic transforms).
The class hierarchy might look like this:
GaussianTransform or GaussianStatisticTransform
GaussianSigmaPointTransform
StudentTransform or StudentStatisticTransform
StudentSigmaPointTransform
There might be a common base class StatisticTransform, but currently I don't see the need for it.
Consequently this will also require redesign of the StudentInference and minor changes in GaussianInference.
StateSpaceInferencesub-classes are specific to a particular density (i.e.GaussianInference,StudentInference). That is, sub-classes are designed with the Bayesian viewpoint, which imposes density on the jointp(x, z). But the same philosophy isn't followed for moment transforms!For reasons of consistency, the same Bayesian philosophy should be reflected in the class hierarchy of the "moment" transforms (they should really be referred to as statistic transforms).
The class hierarchy might look like this:
GaussianTransformorGaussianStatisticTransformGaussianSigmaPointTransformStudentTransformorStudentStatisticTransformStudentSigmaPointTransformThere might be a common base class
StatisticTransform, but currently I don't see the need for it.Consequently this will also require redesign of the
StudentInferenceand minor changes inGaussianInference.The following dictionary might be helpful
_Originally posted by @jacobnzw in https://github.com/_render_node/MDEyOklzc3VlQ29tbWVudDQ0MTYwMjk2OA==/timeline/issue_comment#issuecomment-441602968_