Usage
NMixMCMCwrapper(chain = 1, scale, prior, inits, Cpar, RJMCMC, CRJMCMC, actionAll, nMCMC, keep.chains, PED, dens.zero, lx_w)
Arguments
chain
identification of the chain sampled in a particular call
of this function, usually number like 1, 2, ...
Cpar
a list with the following components
- z0
- $n x p$ matrix with shifted and scaled main limits
of observed intervals.
- z0
- $n x p$ matrix with shifted and scaled upper
limits of observed intervals.
- censor
- $n x p$ matrix with censoring indicators.
- p
- dimension of the response.
- n
- number of observations.
- Cinteger
- a numeric vector with integer prior parameters.
- Cdouble
- a numeric vector with double precission prior
parameters.
- lx_w
- a character vector with levels of an optional factor
covariate on the mixture weights.
scale
a list specifying how to scale the data before running
MCMC. See argument scale in NMixMCMC
prior
a list specifying prior hyperparameters. See argument
prior in NMixMCMC.
inits
a list of length at least chain. Its
chain-th component is used. Each component of the list should
have the structure of init argument of function
NMixMCMC.
RJMCMC
a list specifying parameters for RJ-MCMC.
See argument RJMCMC in NMixMCMC CRJMCMC
a numeric vector with parameters for RJ-MCMC.
actionAll
argument for underlying C++ function.
nMCMC
vector giving the length of MCMC etc.
keep.chains
logical. If FALSE, only summary statistics
are returned in the resulting object. This might be useful in the
model searching step to save some memory.
PED
a logical value which indicates whether the penalized
expected deviance (see Plummer, 2008 for more details)
will be computed (which requires two parallel
chains). Even if keep.chains is FALSE, it is necessary
to keep (for a while) at least some chains to compute PED.
dens.zero
small number (1e-300) to determine whether the
contribution to the deviance ($-log$ density) is equal to
infinity. Such values are trimmed when computing expected deviance.