nsamples.brmsfit

nsamples

An R object

An optional integer vector defining a 
subset of samples to be considered.

subset

A flag indicating whether to also 
count warmup / burn-in samples.

incl_warmup

Further arguments passed to or from other methods.

Extract the number of posterior samples 
stored in a fitted Bayesian model.

Fit Bayesian generalized (non-)linear multivariate multilevel models
using Stan for full Bayesian inference. A wide range of distributions
and link functions are supported, allowing users to fit -- among others --
linear, robust linear, count data, survival, response times, ordinal,
zero-inflated, hurdle, and even self-defined mixture models all in a
multilevel context. Further modeling options include non-linear and
smooth terms, auto-correlation structures, censored data, meta-analytic
standard errors, and quite a few more. In addition, all parameters of the
response distribution can be predicted in order to perform distributional
regression. Prior specifications are flexible and explicitly encourage
users to apply prior distributions that actually reflect their beliefs.
Model fit can easily be assessed and compared with posterior predictive
checks and leave-one-out cross-validation.

nsamples.brmsfit: Number of Posterior Samples

Description

Usage

Arguments

Details