lepidoptera 0.1.2
Bug fixes
- Fixed D-vine conditional sampling for mechanisms with exactly 2
parents (trivariate vine): replaced the
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.
lepidoptera 0.1.1
Bug fixes
- Fixed
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.
- Fixed D-vine conditional sampling for mechanisms with 2+ parents:
unnamed matrices are now passed to
rosenblatt() /
inverse_rosenblatt() to prevent column reordering by name
in newer rvinecopulib versions.
- Removed reference to non-exported
rvinecopulib::bicop_family_list in
list_copula_families().
lepidoptera 0.1.0
Initial release
- Core system API:
new_system(),
add_feature(), add_dependency(),
finalize_system().
- Pre-built mechanism library covering all nine parent-type ×
child-type combinations:
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.- Intervention types:
do_fix(),
do_distribution(), shift(),
mechanism_override().
propagate() with mode = "full" (ATE /
independent interventional draws) and mode = "partial" (ITE
/ frozen exogenous noise counterfactuals).- Vine copula mechanism via
copula_mechanism(), backed by
rvinecopulib (optional dependency).
- Predictive model integration via
model_mechanism() and
learned_mechanism().
- Language model mechanism via
llm_mechanism().
- JSON / YAML serialisation via
export_system() /
import_system().
- DAG visualisation via
plot_graph() (requires
igraph).