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coef() methods and tidy.mcmcr() gain a
directional_information argument. When TRUE
the svalue column reports extras::directional_information()
in place of extras::svalue()
(#71, #84). The default is currently FALSE and will change
to TRUE in a future release; calling either function
without setting directional_information now signals a
deprecation warning so the change can be made explicit.tidy.mcmcr() now defaults to
simplify = TRUE, matching the nlist
tidy() methods.coef(simplify = FALSE), deprecated in 0.4.1, is now
defunct (#74).parameters() and
parameters<-(), which are defunct in term, have been
removed (#85).rhat.mcmcrs(bound = TRUE) now returns a named list of
scalars rather than a single scalar; use
rhat(x, bound = TRUE)$bound for the previous behavior. The
change is signaled with a warning (#74).The following, soft-deprecated in 0.2.1, now warn on every use (#72):
terms(); use as_term() instead.zero(); use fill_all() instead.check_mcmcarray() and check_mcmcr(); use
chk_mcmcarray() and chk_mcmcr() instead.subset(iterations = ) and
subset(parameters = ); use subset(iters = )
and subset(pars = ) instead.pars(terms = ); use
term::pars_terms(as_term(x)) for terms = TRUE,
and pars(x) for terms = FALSE.extras is now required at version 0.10.0 or later, and
nlist at version 0.5.0 or later.bound = TRUE rhat() now also returns
rhat values for separate analyses.bound = TRUE and as_df = TRUE
rhat() now returns a data.frame with the rhat values for
the separate and combined analyses.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()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.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().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.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().These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.