Multinomial Polya node
The MultinomialPolya node implements a Multinomial likelihood with PolyaGamma augmentation for Bayesian inference. This node is particularly useful for modeling count data with overdispersion and performing Multinomial regression.
ReactiveMP.MultinomialPolya — TypeMultinomialPolyaA node type representing a MultinomialPolya likelihood with linear predictor through softmax. A Normal prior on the weights is used. The prior is augmented with a PolyaGamma distribution, which is used for modeling count data with overdispersion. This implementation follows the PolyaGamma augmentation scheme for Bayesian inference. Can be used for Multinomial regression. Uses cubature integration for the PolyaGamma augmentation scheme with a default of 21 points. Use MultinomialPolyaMeta to change the number of cubature points.
ReactiveMP.MultinomialPolyaMeta — TypeMultinomialPolyaMetaA structure that contains the meta-parameters for the MultinomialPolya node.
Fields
ncubaturepoints::Int: The number of cubature points used for integration in the PolyaGamma augmentation scheme.
ReactiveMP.MULTINOMIAL_POLYA_CUBATURE_POINTS — ConstantMULTINOMIAL_POLYA_CUBATURE_POINTSThe number of cubature points used for integration in the PolyaGamma augmentation scheme.