posterior_predict.hsstan: Posterior predictive distribution

In hsstan: Hierarchical Shrinkage Stan Models for Biomarker Selection

Description

Draw from the posterior predictive distribution of the outcome.

Usage

## S3 method for class 'hsstan'
posterior_predict(object, newdata = NULL, nsamples = NULL, seed = NULL, ...)

Arguments

object	An object of class hsstan.
newdata	Optional data frame containing the variables to use to predict. If NULL (default), the model matrix is used. If specified, its continuous variables should be standardized, since the model coefficients are learnt on standardized data.
nsamples	A positive integer indicating the number of posterior samples to use. If NULL (default) all samples are used.
seed	Optional integer defining the seed for the pseudo-random number generator.
...	Currently ignored.

Value

A matrix of size S by N, where S is the number of simulations from the posterior predictive distribution, and N is the number of data points.

Examples

# continued from ?hsstan
posterior_predict(hs.biom)

hsstan documentation built on Sept. 16, 2021, 9:11 a.m.