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rosenblatt() /
inverse_rosenblatt() pipeline—whose behaviour changed for
single-row matrices in newer rvinecopulib versions—with
an explicit sequential h-function algorithm using
pair_copulas(). Spearman correlations in the simulated
output now correctly reflect the fitted dependence structure.copula_mechanism() with non-Gaussian families:
hbicop() now returns a numeric vector in newer
rvinecopulib versions; the bivariate path handles both
vector and matrix return types.rosenblatt() /
inverse_rosenblatt() to prevent column reordering by name
in newer rvinecopulib versions.rvinecopulib::bicop_family_list in
list_copula_families().new_system(),
add_feature(), add_dependency(),
finalize_system().linear_gaussian,
multinomial_logit, ordered_logit,
group_effect, categorical_transition,
accessible via mechanism_library_get().simulate() for population-level data generation under
topological ordering with per-unit reproducible seeds.do_fix(),
do_distribution(), shift(),
mechanism_override().propagate() with mode = "full" (ATE /
independent interventional draws) and mode = "partial" (ITE
/ frozen exogenous noise counterfactuals).copula_mechanism(), backed by
rvinecopulib (optional dependency).model_mechanism() and
learned_mechanism().llm_mechanism().export_system() /
import_system().plot_graph() (requires
igraph).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.