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xp_from_bbr() converts a ‘bbr’ model directly into an
xp_xtras object.add_cov_association(), prm_cov() family) with
xplot_forest() / cov_forest() visualization;
see the new parameter-associations vignette.cormat() visualizes the parameter
correlation/covariance matrix, for both NONMEM and nlmixr2 models.catdv_vs_occ() and catdv_vs_ipred() add
categorical DV diagnostic plots (observed-vs-predicted trend across
occasions, and binned calibration).left_join_x() backfills missing variables into an xpdb
via a coalescing left join.set_default_labs(), add_watermark(),
ggsave_xp()), configurable via
set_xtras_options() and auto-applied on print/save. See the
new plot-output vignette.patch_condn() corrects
‘xpose’s condition number calculation for multi-method NONMEM runs, applied automatically byas_xpdb_x()`.focus_function() / focus_qapply() now
support output-generating functions (plots, tables), not just
xpdb-transforming ones.logLik(), AIC(), and
BIC() methods for xpose_data and
xpose_set objects.ind_plots_sample() plots a representative (optionally
stratified) sample of individuals instead of the whole dataset.plot.xpose_data() runs a configurable batch of
diagnostic plots in one call.process_preset() family saves and replays a reusable
xpdb processing pipeline by name, optionally persisted across
sessions.set_dv_probs() no longer crashes when
.problem is omitted.conflicted preferences are now re-applied regardless of
package attach order, fixing spurious “found in 2 packages” errors.%p%.as_xpdb_x() / check_xpdb_x()
erroring on xpose_data objects with no table data.xplot_pairs() silently ignoring a custom
catcont_opts$other_fun, and removed an unreachable leftover
duplicate-axis-label block in roc_by_mod().nlmixr_example() / nlmixr2_example() to avoid
loading nlmixr2est when not installed.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.