(GitHub issue/PR numbers in parentheses)
mcmc_parcoord()
for parallel coordinates plots of MCMC draws (optionally including HMC/NUTS diagnostic information). (#108)mcmc_scatter
gains an np
argument for specifying NUTS parameters, which allows highlighting divergences in the plot. (#112)_data
don’t make the plots, they just return the data prepared for plotting (more of these to come in future releases):
ppc_intervals_data()
(#101)ppc_ribbon_data()
(#101)mcmc_parcoord_data()
(#108)mcmc_rhat_data()
(#110)mcmc_neff_data()
(#110)ppc_stat_grouped()
, ppc_stat_freqpoly_grouped()
gain a facet_args
argument for controlling ggplot2 faceting (many of the mcmc_
functions already have this).divergences
argument to mcmc_trace()
has been deprecated in favor of np
(NUTS parameters) to match the other functions that have an np
argument.mcmc_rhat()
(#105).(GitHub issue/PR numbers in parentheses)
bayesplot::theme_default
is now set as the default ggplot2 plotting theme when bayesplot is loaded, which makes changing the default theme using ggplot2::theme_set
possible. Thanks to @gavinsimpson. (#87)mcmc_hist
and mcmc_hist_by_chain
now take a freq
argument that defaults to TRUE
(behavior is like freq
argument to R’s hist
function).ts
object for y
in PPC plots no longer results in an error. Thanks to @helske. (#94)mcmc_intervals
doesn’t use round lineends anymore as they slightly exaggerate the width of the intervals. Thanks to @tjmahr. (#96)(GitHub issue/PR numbers in parentheses)
A lot of new stuff in this release:
divergences
is specified in call to mcmc_trace
but there are not actually any divergent transitions.merge_chains
argument to mcmc_nuts_energy
now defaults to FALSE
.mcmc_*
functions, transformations are recycled if transformations
argument is specified as a single function rather than a named list. Thanks to @tklebel. (#64)ppc_violin_grouped
there is now the option of showing y
as a violin, points, or both. Thanks to @silberzwiebel. (#74)color_scheme_get
now has an optional argument i
for selecting only a subset of the colors.mcmc_pairs
, which is essentially a ggplot2+grid implementation of rstan’s pairs.stanfit
method. (#67)mcmc_hex
, which is similar to mcmc_scatter
but using geom_hex
instead of geom_point
. This can be used to avoid overplotting. (#67)overlay_function
convenience function. Example usage: add a Gaussian (or any distribution) density curve to a plot made with mcmc_hist
.mcmc_recover_scatter
and mcmc_recover_hist
, which are similar to mcmc_recover_intervals
and compare estimates to “true” values used to simulate data. (#81, #83)ppc_rootogram
for use with models for count data. Thanks to @paul-buerkner. (#28)ppc_bars
, ppc_bars_grouped
for use with models for ordinal, categorical and multinomial data. Thanks to @silberzwiebel. (#73)ppc_loo_pit
for assessing the calibration of marginal predictions. (#72)ppc_loo_intervals
, ppc_loo_ribbon
for plotting intervals of the LOO predictive distribution. (#72) (GitHub issue/PR numbers in parentheses)
png
device. Thanks to TJ Mahr. (#51)xaxis_title(FALSE)
and yaxis_title(FALSE)
now set axis titles to NULL
rather than changing theme elements to element_blank()
. This makes it easier to add axis titles to plots that don’t have them by default. Thanks to Bill Harris. (#53)divergences
to mcmc_trace
function. For models fit using HMC/NUTS this can be used to display divergences as a rug at the bottom of the trace plot. (#42)stat
argument for all ppc_stat_*
functions now accepts a function instead of only the name of a function. (#31)