mcmc_thin: Thin a mcmc chain

In mrc-ide/gonovax: Deterministic Compartmental Model of Gonorrhoea with Vaccination

Thin a mcmc chain

Description

Thin results of running [mcmc()].‘mcmc_thin' takes every 'thin'’th sample, while 'mcmc_sample' randomly selects a total of 'n_sample' samples.

Usage

mcmc_thin(object, burnin = NULL, thin = NULL)

mcmc_sample(object, n_sample, burnin = NULL)

Arguments

object	Results of running [mcmc()]
burnin	Optional integer number of iterations to discard as "burn-in". If given then samples '1:burnin' will be excluded from your results. Remember that the first sample represents the starting point of the chain. It is an error if this is not a positive integer or is greater than or equal to the number of samples (i.e., there must be at least one sample remaining after discarding burnin).
thin	Optional integer thinning factor. If given, then every ‘thin'’th sample is retained (e.g., if 'thin' is 10 then we keep samples 1, 11, 21, ...).
n_sample	The number of samples to draw from 'object' *with replacement*. This means that 'n_sample' can be larger than the total number of samples taken (though it probably should not)

mrc-ide/gonovax documentation built on April 17, 2025, 8:33 p.m.