BetaDanish 0.2.0
Major new functionality
- Bayesian inference:
bayes_betadanish()
provides random-walk Metropolis sampling for the Exponentiated Danish
submodel and the full four-parameter Beta-Danish model with vague Gamma
priors.
- Competing risks rewrite:
fit_bd_competing() now uses bound-constrained multi-start
L-BFGS-B optimization. New cif_compare() overlays fitted
cumulative incidence functions against the Aalen-Johansen estimator and
reports Gray’s test.
- Structural properties: closed-form Shannon entropy
(
bd_entropy_shannon()), order-statistic densities
(bd_order_stat_pdf()), mean residual life, hazard-shape
classification, and stress-strength reliability.
- Diagnostics: Cox-Snell residual plots for both AFT
(
plot.bd_aft()) and cure (plot.bd_cure())
fits.
- Bootstrap confidence intervals for AFT and cure
models.
- Finite-sample simulation-study runner for Table 5.5
of the underlying thesis.
Vignettes
Three new vignettes have been added:
- “Bayesian Estimation with BetaDanish”
- “Competing Risks with the Beta-Danish Distribution”
- “Cure Models with the Beta-Danish Distribution”
Bug fixes
summary.bd_aft() and summary.bd_cure() now
apply the delta-method back-transform so that reported standard errors
are on the natural parameter scale, not the log scale.
report_betadanish() no longer prints NULL for AIC and
BIC.
dbetadanish() log-pdf is now numerically stable in the
right tail.
qbetadanish() clamps p to the unit
interval.
Infrastructure
- Continuous integration via GitHub Actions on four OS/R
configurations: ubuntu-release, ubuntu-devel, macOS-release, and
windows-release.
- Test coverage reporting via Codecov.
- Online package website built with pkgdown.
- All
Suggests packages used via
requireNamespace() guards at the call sites.
BetaDanish 0.1.0
- First public release.
- Implements the four-parameter Beta-Danish distribution and its
three-parameter Exponentiated Danish submodel for survival and
reliability analysis.
- Maximum-likelihood estimation, goodness-of-fit, model comparison,
and visualization.
- Built-in datasets: remission, carbon_fibres, transplant, aarset,
leukemia, melanoma, brain_cancer.