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