| as.mcmc.bkmrfit {bkmrhat} | R Documentation |
Convert bkmrfit to mcmc object for coda MCMC diagnostics
Description
Converts a kmrfit (from the bkmr package) into
an mcmc object from the coda package. The
coda package enables many different types of single chain MCMC
diagnostics, including geweke.diag, traceplot and
effectiveSize. Posterior summarization is also available,
such as HPDinterval and summary.mcmc.
Usage
## S3 method for class 'bkmrfit'
as.mcmc(x, iterstart = 1, thin = 1, ...)
Arguments
x |
object of type kmrfit (from bkmr package) |
iterstart |
first iteration to use (e.g. for implementing burnin) |
thin |
keep 1/thin % of the total iterations (at regular intervals) |
... |
unused |
Value
An mcmc object
Examples
# following example from https://jenfb.github.io/bkmr/overview.html
set.seed(111)
library(coda)
library(bkmr)
dat <- bkmr::SimData(n = 50, M = 4)
y <- dat$y
Z <- dat$Z
X <- dat$X
set.seed(111)
fitkm <- kmbayes(y = y, Z = Z, X = X, iter = 500, verbose = FALSE,
varsel = FALSE)
mcmcobj <- as.mcmc(fitkm, iterstart=251)
summary(mcmcobj) # posterior summaries of model parameters
# compare with default from bkmr package, which omits first 1/2 of chain
summary(fitkm)
# note this only works on multiple chains (see kmbayes_parallel)
# gelman.diag(mcmcobj)
# lots of functions in the coda package to use
traceplot(mcmcobj)
# will also fail with delta functions (when using variable selection)
try(geweke.plot(mcmcobj))
[Package bkmrhat version 1.1.3 Index]