When bound = TRUE
rhat()
now also returns rhat values for separate analyses.
When bound = TRUE
and as_df = TRUE
rhat()
now returns a data.frame with the rhat values for the separate and combined analyses.
Merge pull request #52 from poissonconsulting/description-contr.
add contributors
update rcmd check and documentation
Made changes to Actions using UsePois and Files were created
fill_na()
for mcarray
, mcmcarray
and mcmcr
.as.mcmcarray.mcmc()
(and as.mcmcr.mcmc()
) so now returns an mcmcarray
(and mcmcr
) object with no terms.tidy.mcmcr()
.simplify = FALSE
argument to coef()
and tidy()
and soft-deprecated if not TRUE
....
optional arguments for fun = median
argument to estimates()
.as_nlists.mcmc.list()
to nlist package.as_mcmc_list.mcmr()
.nlist
as_nlist.mcmc()
and as_nlist.mcmc.list()
as_nlists.mcmc()
as.term.mcmc()
and as.term.mcmc.list()
bind_iterations.mcmc()
and bind_iterations.mcmc.list()
collapse_chains.default()
and collapse_chains.mcmc.list()
Changed
npdims.mcmc.list()
to return character vector (as opposed to list)collapse_chains.mcmc.list()
to return an mcmc.list object with one chain (as opposed to an mcmc object)estimates()
from object
to x
.scalar_only = FALSE
argument of pars()
to scalar = NA
.estimates()
so now checks fun returns scalar numeric.Soft-deprecated
pvalue()
for extras::pvalue()
.zero()
for fill_all()
.check_mcmcarray()
and check_mcmcr()
for chk_mcmcarray()
and chk_mcmcr()
.iterations
argument with iters
in subset()
.parameters
argument with pars
in subset()
.Added
vld_()
and chk_()
functions for mcmcarray and mcmcr objects.scalar = NULL
argument to pars()
and npars()
.na_rm = NA
argument to esr()
and rhat()
.as_df = FALSE
arg to esr()
for mcarray, mcmc and mcmc.list.Moved
nchains()
, niters()
, collapse_chains()
and split_chains()
etc to universals package.check_mcmcr()
and check_mcmcarray()
.converged()
.as.mcmc.mcmc.list()
, thin.mcmc()
and thin.mcmc.list()
as now defined by coda.as.mcmc.list.mcarray()
as clashes with rjags version.mcmc_aperm()
function to transpose parameter dimensions.npdims()
function to get number of parameter dimensions.by = TRUE
argument to mcmc_map()
function.rhat()
now returns minimum of 1.subset()
and parameters()
for mcmcrs object.bound = FALSE
argument to rhat.mcmcrs()
and converged.mcmcrs()
functions.error()
with err::err()
.