sampler.LeafVarianceModel

sampler.LeafVarianceModel()

Wrapper around methods / functions for sampling a “leaf scale” model for the variance term of a Gaussian leaf model with inverse gamma prior.

Methods

Name Description
sample_one_iteration Sample one iteration of a forest leaf model’s variance parameter (assuming a location-scale leaf model, most commonly N(0, tau))

sample_one_iteration

sampler.LeafVarianceModel.sample_one_iteration(forest, rng, a, b)

Sample one iteration of a forest leaf model’s variance parameter (assuming a location-scale leaf model, most commonly N(0, tau))

Parameters

Name Type Description Default
forest Forest stochtree object storing the “active” forest being sampled required
rng RNG stochtree object storing C++ random number generator to be used sampling algorithm required
a float Shape parameter for the inverse gamma leaf scale model required
b float Scale parameter for the inverse gamma leaf scale model required

Returns

Name Type Description
float One draw from a Gibbs sampler for the leaf scale model, which depends on the rest of the model only through its respective forest.