Nothing
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.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.fit_*, em_*, simulate_*, logL_*).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.labor_force_cat (categorical labor-force sequences) and
race_100km (continuous 100km race split times).Any scripts or data that you put into this service are public.
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