antedep 0.1.0
New features
fit_inad() gains a nb_inno_size_ub
argument (default 50) that caps the upper bound of the negative-binomial
innovation size parameter during optimization, improving numerical
stability for near-Poisson data.test_order_gau() accepts order_null and
order_alt as convenience aliases for p and the
absolute alternative order; both are also returned in the result
object.
Bug fixes
ci_inad(): fixed a sign error in the observed Fisher
information for the negative-binomial innovation size parameter; the
Hessian term (r + u) / (r + λ)² was added instead of
subtracted, producing confidence intervals that were too wide.ci_inad(): the numerical second derivative for
nb_inno_size CIs now retries with progressively smaller
step sizes (×0.1, ×0.01) before falling back to NA, avoiding spurious
failures when the default step lands in a non-finite region.test_homogeneity_inad(): degrees of freedom for LRT
tests involving innovation = "nbinom" are now computed from
the actual number of NB size parameters in the fitted models rather than
assuming a fixed count of 1. This corrects LRT statistics and p-values
whenever nb_inno_size is fitted as a time-varying
vector.ci_inad() tau profile CI: nb_inno_size
(negative-binomial innovation dispersion) is now held fixed at its
full-model MLE during profile refits, consistent with the
constrained-fit paradigm used throughout the package. Previously it was
re-optimised as a nuisance parameter, which could widen the interval to
the point of crossing zero even when the LRT clearly rejects the null
(Variant 1 vs Variant 2 fix).ci_inad() tau profile CI: the bracket search in
.ci_tau_profile_inad no longer imposes an artificial upper
cap (max(|tau_mle| + 1, 1)) on the search range. The
maximum bracket iterations are increased from 20 to 50 and the initial
step size is set to max(0.1, |tau_mle| * 0.2), preventing
the search from stalling for large or near-zero MLEs.
Initial release
- Initial CRAN submission candidate for Gaussian AD, categorical AD,
and INAD workflows.
- Added/expanded examples for key user-facing modeling functions
(
fit_*, em_*, simulate_*,
logL_*).
- Refreshed missing-data notes and harmonized documentation links and
metadata.
logL_gau() default missing-data behavior is now
na_action = "fail" (previously marginalization-first in
earlier drafts). For missing inputs, pass
na_action = "marginalize" or
na_action = "complete" explicitly.- Added packaged datasets
labor_force_cat (categorical
labor-force sequences) and race_100km (continuous 100km
race split times).