pgmultinom: Bayesian categorical regression model with polya-gamma data...

In lvhoskovec/pgmultinomr: Fit Bayesian Categorical Regression Model with Polya-Gamma Augmentation

Description

Bayesian categorical regression model with polya-gamma data augmentation

Usage

pgmultinom(niter, priors = NULL, y, x, w = NULL, intercept = TRUE)

Arguments

niter	number of iterations
priors	list of priors
y	matrix of outcome data, with possible missing observations denoted by NA
x	matrix of exposure data
w	(optional) matrix of covariate data
intercept	logical; if TRUE, include an intercept when fitting model

Value

a list with components

• y_original: matrix, categorical outcome data y for fitting

• beta: list with components, the matrix of estimated exposure regression coefficients at each iteration

• beta.vec: list with components, the vectorized estimated exposure regression coefficients at each iteration

• gamma: list with components, the matrix of estimated covariate regression coefficients at each iteration

• gamma.vec: list with components, the vectorized estimated covariate regression coefficients at each iteration

• y.save: list with components, the matrix of outcomes with imputations at each iteration

lvhoskovec/pgmultinomr documentation built on Dec. 21, 2021, 12:45 p.m.