evbsreg: Local Influence Diagnostics for the Extreme-Value
Birnbaum-Saunders Regression Model
Implements local influence diagnostics for the Extreme-Value
Birnbaum-Saunders (EVBS) regression model: joint maximum likelihood
estimation, conformal normal curvature diagnostics under three
perturbation schemes (case-weight, response variable, and explanatory
variable), randomized quantile residuals with simulation envelope,
Monte Carlo simulation utilities, and publication-quality density and
diagnostic plots. Version 1.1.0 adds the density, distribution and
quantile functions, the finite upper endpoint, return levels and
expected shortfall, block bootstrap standard errors for serially
dependent series, local influence diagnostics for the generalized
extreme-value regression model, and a GAMLSS family allowing the
tail-shape parameter to depend on covariates. Version 1.2.0 adds a
prospective control chart for endpoint identifiability. The methods
are described in Ospina, Lima, Barros, and Macedo (2026, submitted)
and are applied to monthly maximum wind gust data from Itajai, Brazil.
| Version: |
1.2.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
stats, graphics, SpatialExtremes, ggplot2 |
| Suggests: |
gamlss, grDevices, knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-09-18 |
| DOI: |
10.32614/CRAN.package.evbsreg |
| Author: |
Raydonal Ospina 
[aut, cre] |
| Maintainer: |
Raydonal Ospina <raydonal at de.ufpe.br> |
| BugReports: |
https://github.com/Raydonal/evbsreg/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/Raydonal/evbsreg,
https://raydonal.github.io/evbsreg/ |
| NeedsCompilation: |
no |
| Citation: |
evbsreg citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
evbsreg results |
Documentation:
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