raydonal.r-universe.dev

[cran] simplexgof 0.1.0

raydonal@de.ufpe.br (Raydonal Ospina) — Fri, 19 Jun 2026 12:20:02 GMT

Implements the bootstrap-calibrated local-influence goodness-of-fit test for simplex regression models with constant or varying dispersion, following the local influence approach of Zhu and Zhang (2004) and the simplex regression model of Barndorff-Nielsen and Jorgensen (1991) . The test statistic aggregates individual local-influence measures under case-weight perturbation. Because the first-order asymptotic normal calibration is severely liberal in finite samples, a parametric bootstrap calibration is provided that restores accurate size control and delivers high power against omitted covariates, neglected dispersion, and distributional misspecification. Plotting functions reproduce the figures and tables of the companion methodological paper. Computational kernels are implemented in 'C++' via 'Rcpp' and 'RcppArmadillo' for speed, and two real datasets are bundled.

[cran] prLogistic 2.0.2

raydonal@de.ufpe.br (Raydonal Ospina) — Fri, 19 Jun 2026 12:00:02 GMT

Estimates adjusted prevalence ratios (PR) and their confidence intervals from logistic regression models, addressing the well-known limitation of odds ratios (OR) as approximations to PR in cross-sectional studies with common outcomes. Supports independent observations (glm()), clustered/multilevel data (glmer() from 'lme4'), longitudinal data via Generalised Estimating Equations (geeglm() from 'geepack'), and complex survey designs (svyglm() from 'survey'). Inference is available via the delta method (conditional and marginal standardisation) and via bootstrap (normal-approximation and percentile intervals). Continuous covariates are handled through user-specified or median-based reference values; flexible baseline specification allows any reference category to be chosen for factor predictors. Based on the methodology described in Amorim & Ospina (2021) .

[raydonal] logcumulant 0.1.0

raydonal@de.ufpe.br (Raydonal Ospina) — Sat, 06 Jun 2026 15:26:48 GMT

A family of three complementary goodness-of-fit tests based on an adaptation of Hotelling's T-squared statistic applied to vectors of sample log-cumulants (Mellin statistics) for positive-support reliability data. The package provides the asymptotic chi-squared reference and parametric bootstrap p-values for reliable finite-sample inference, covering the Weibull, Frechet, Gamma, Inverse-Gamma, Log-Normal, and Log-Logistic families. It also provides three diagnostic diagrams (log-cumulant, kurtosis-skewness, and coefficient-of-variation) with bootstrap concentration ellipses, in the spirit of moment-ratio diagrams. Methods are described in Santos, Ospina, Espinheira and Oliveira (2025).