as.matrix.htlr.fit: Create a Matrix of Markov Chain Samples

In HTLR: Bayesian Logistic Regression with Heavy-Tailed Priors

Create a Matrix of Markov Chain Samples

Description

The Markov chain samples (without warmup) included in a htlr.fit object will be coerced to a matrix.

Usage

## S3 method for class 'htlr.fit'
as.matrix(x, k = NULL, include.warmup = FALSE, ...)

Arguments

x	An object of S3 class htlr.fit.
k	Coefficients associated with class k will be drawn. Must be a positive integer in 1,2,...,C-1 for C-class traning labels (base class 0 can not be chosen). By default the last class is selected. For binary logistic model this argument can be ignored.
include.warmup	Whether or not to include warmup samples
...	Not used.

Value

A matrix with (p + 1) columns and i rows, where p is the number of features excluding intercept, and i is the number of iterations after burnin.

Examples

## No. of features used: 100; No. of iterations after burnin: 15 
fit <- htlr(X = colon$X, y = colon$y, fsel = 1:100, iter = 20, warmup = 5)

dim(as.matrix(fit))
  

HTLR documentation built on Oct. 22, 2022, 5:05 p.m.