transform_gibbs_samples: Transformation of Gibbs samples

In RprobitB: Bayesian Probit Choice Modeling

Transformation of Gibbs samples

Description

This function normalizes, burns and thins the Gibbs samples.

Usage

transform_gibbs_samples(gibbs_samples, R, B, Q, normalization)

Arguments

gibbs_samples	The output of gibbs_sampling, i.e. a list of Gibbs samples for Sigma, alpha (if P_f>0), s, z, b, Omega (if P_r>0).
R	The number of iterations of the Gibbs sampler.
B	The length of the burn-in period, i.e. a non-negative number of samples to be discarded.
Q	The thinning factor for the Gibbs samples, i.e. only every Qth sample is kept.
normalization	An object of class RprobitB_normalization, which can be created via RprobitB_normalization.

Value

A list, the first element gibbs_sampes_raw is the input gibbs_samples, the second element is the normalized, burned, and thinned version of gibbs_samples called gibbs_samples_nbt. The list gets the class RprobitB_gibbs_samples.

RprobitB documentation built on Nov. 10, 2022, 5:12 p.m.