extract_stan: Extract chains of an 'stanfit' object implemented in 'rstan'...

In bayesforecast: Bayesian Time Series Modeling with Stan

Extract chains of an stanfit object implemented in rstan package

Description

Extract chains of an stanfit object implemented in rstan package

Usage

extract_stan(
  object,
  pars,
  permuted = TRUE,
  inc_warmup = FALSE,
  include = TRUE,
  ...
)

Arguments

object	a varstan object
pars	n optional character vector providing the parameter names (or other quantity names) of interest. If not specified, all parameters and other quantities are used. The log-posterior with name lp__ is also included.
permuted	a logical scalar indicating whether the draws after the warm-up period in each chain should be permuted and merged. If FALSE, the original order is kept. For each stanfit object, the permutation is fixed (i.e., extracting samples a second time will give the same sequence of iterations).
inc_warmup	a logical scalar indicating whether to include the warm-up draws. This argument is only relevant if permuted is FALSE.
include	a logical scalar indicating whether the parameters named in pars should be included (TRUE) or excluded (FALSE).
...	Further arguments passed to extract function.

Value

a list with the posterior samples of the provided parameters.

Author(s)

Asael Alonzo Matamoros

Examples

 # Fitting a GARCH(1,1) model
 dat = garch(ipc,order = c(1,1,0))
 fit2 = varstan(dat,iter = 500,chains = 1)

 # Extracting the mean parameter
 mu0 = extract_stan(fit2,pars = "mu0")

bayesforecast documentation built on June 8, 2025, 10:42 a.m.