A convenient wrapper function (posterior) to sample the posterior using MCMC in rstan
and returns a stanfit object for diagnostics. Use RCMstan to update the RCM and the enclosed operating model
with MCMC samples..
Usage
posterior(x, ...)
# S4 method for class 'RCModel'
posterior(
x,
priors_only = FALSE,
laplace = FALSE,
chains = 2,
iter = 2000,
warmup = floor(iter/2),
thin = 5,
seed = 34,
init = "last.par.best",
cores = chains,
...
)
# S4 method for class 'Assessment'
posterior(x, priors_only = FALSE, ...)
RCMstan(RCModel, stanfit, sim, cores = 1, silent = FALSE)Arguments
- x
An object of class Assessment or RCModel.
- ...
Additional arguments to pass to
rstan::samplingviatmbstan::tmbstan.- priors_only
Logical, whether to set the likelihood to zero and sample the priors only.
- laplace
Logical, whether to do the Laplace approximation for random parameters.
- chains
The numer of MCMC chains.
- iter
The number of iterations for each chain, including warmup.
- warmup
The number of burnin iterations
- thin
The frequency at which iterations are kept (e.g.,
5saves every fifth iteration)- seed
Seed for random number generator during the MCMC.
- init
The initial values of parameters for starting the MCMC chain. See
tmbstan::tmbstan.- cores
The number of cores for running in parallel, e.g., one core per MCMC chain. Used in
RCMstanfor reconstructing the population.- RCModel
An object of class
RCModel- stanfit
An object of class
stanfitreturned byposterior.- sim
A matrix of
RCModel@OM@nsimrows and 2 columns that specifies the samples used to update the operating model. The first column specifies the chain and the second columns specifies the MCMC iteration.- silent
Logical to indicate if progress messages should be printed to console.
Value
posterior returns an object of class stanfit. See class?stanfit.
RCMstan returns an updated RCModel.
Online Documentation
A vignette on the steps to run the MCMC is available on the openMSE website.