The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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).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.