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().