The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
draws_array objects.exclude option to subset_draws(),
which can be used to exclude the matched selection.are_log_weights option to
pareto_smooth(), which is necessary for correct Pareto
smoothing computation if the input vector consists of log weights.pareto_smooth option to
weight_draws(), to Pareto smooth weights before adding to a
draws object.pareto_khat(), pareto_khat_threshold(),
pareto_min_ss(),
pareto_convergence_rate())thin_draws() now automatically thins draws based on ESS
by default, and non-integer thinning is possible.rvars can now be done with the
base matrix multiplication operator (%*%) instead of
%**% in R >= 4.3.variables(), variables<-(),
set_variables(), and nvariables() now support
a with_indices argument, which determines whether variable
names are retrieved/set with ("x[1]", "x[2]"
…) or without ("x") indices (#208).extract_variable_array() function to extract
variables with indices into arrays of iterations x chains x any
remaining dimensions (#340).factor variables
(draws_df, draws_list, and
draws_rvars), extract_variable() and
extract_variable_matrix() can now return
factors.rhat_nested
(#256)rvars using
rvars (#282):
x[i] or x[i] <- y where i
is a scalar logical rvar slices (or updates) x
by its draws. Thus, if y <- x[i], then y is
the same shape as x but with sum(i)
draws.x[[i]] or x[[i]] <- y where
i is a scalar numeric rvar slices (or updates)
x by selecting the ith element within each
corresponding draw. Thus, if y <- x[[i]], then
y is an rvar of length 1.rvar_ifelse(), which is a variant of
ifelse() that accepts (and returns) rvars
(#282).rvars has been made faster.rfun() works with primitive functions (#290) and
dots arguments (#291).vctrs::vec_proxy_equal(),
vctrs::vec_proxy_compare(), and
vctrs::vec_proxy_order().cbind(<rvar>),
rbind(<rvar>), and chol(<rvar>)
for R 4.4 (#304).bind_draws(<draws_rvars>) regenerates
draw ids when binding along chains or draws; this also fixes a bug in
split_chains(<draws_rvars>) (#300).tibble::num() formatting to output from
summarise_draws() until print() is called so
that summary output can be easily converted to a vanilla data frame
(#275).rvar_factor() and rvar_ordered()
subtypes of rvar() that work analogously to
factor() and ordered() (#149). See the new
section on rvar_factors in
vignette("rvar").draws_df(), draws_list(), and
draws_rvars() formats now support discrete variables stored
as factors / ordereds (or
rvar_factors / rvar_ordereds). If converted to
formats that do not support discrete variables with named levels
(draws_matrix() and draws_array()),
factor-like variables are converted to numerics.match() and %in% generic and added
support for rvars to both functions.modal_category(), entropy(), and
dissent() functions for summarizing discrete draws.bind_draws() (#253).summarise_draws output via
tibble::num.print.rvar() and format.rvar() now default
to a smaller number of significant digits in more cases, including when
printing in data frames. This is controlled by the new
"posterior.digits" option (see
help("posterior-package")).vec_proxy.rvar() and
vec_restore.rvar(), improving performance of
rvars in tibbles (and elsewhere
vctrs is used).as_draws_rvars() preserves dimensions of
length-1 arrays (#265).rvar,
vctrs, dplyr, and ggplot2 (#267,
#269).for_each_draw(x, expr), which executes
expr once for each draw of x, exposing
variables in x as arrays of the shape implied by the
indices in their names (#224).subset_draws(), thin_draws(),
and resample_draws() for rvars (#225).weights to be optional in
resample_draws() (#225).drop() for
rvars.draws_list objects. (#229,
#250)diag() for
rvars (#246).as_draws_rvars(),
including nested use of [, like x[y[1],2]
(#243).rvars with ndraws() > 1
(#242).rvars can be cast to draws
formats (#242).rvars with more than 1 dimension
as scalars when casting to other formats (#248).mcse_sd function to not make a normality
assumption. (#232)draws_list objects.NULL in
mutate_variables. (#222)rvar and
distributional::dist_sample (#109)bind_draws.draws_df when
binding more than two objects thanks to Jouni Helske (#204)pillar::glimpse() when used on a data
frame containing rvars (#210)"draws" and "draws_df" classes from
draws_df objects if meta data columns are removed by a
dplyr operation (#202)print.draws_df() on objects with
unrepaired draws (#217)variance() works properly with
summarise_draws() (#219)matrixStats to speed up convergence functions
(#190) and rvar summaries (#200)as_draws_rvars() works on lists of lists
(#192)rvar_rng
(#195)subset_draws() respects input variable
order, thanks to Karl Dunkle Werner and Alexey Stukalov (#188)ess_tail. (#198)rvars being
unnecessarily slow (#179)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.