Package: gamlssx 1.0.1

gamlssx: Generalized Additive Extreme Value Models for Location, Scale and Shape

Fits generalized additive models for the location, scale and shape parameters of a generalized extreme value response distribution. The methodology is based on Rigby, R.A. and Stasinopoulos, D.M. (2005), <doi:10.1111/j.1467-9876.2005.00510.x> and implemented using functions from the 'gamlss' package <doi:10.32614/CRAN.package.gamlss>.

Authors:Paul J. Northrop [aut, cre, cph], Jennifer Ji [aut]

gamlssx_1.0.1.tar.gz
gamlssx_1.0.1.zip(r-4.5)gamlssx_1.0.1.zip(r-4.4)gamlssx_1.0.1.zip(r-4.3)
gamlssx_1.0.1.tgz(r-4.4-any)gamlssx_1.0.1.tgz(r-4.3-any)
gamlssx_1.0.1.tar.gz(r-4.5-noble)gamlssx_1.0.1.tar.gz(r-4.4-noble)
gamlssx_1.0.1.tgz(r-4.4-emscripten)gamlssx_1.0.1.tgz(r-4.3-emscripten)
gamlssx.pdf |gamlssx.html✨
gamlssx/json (API)

# Install 'gamlssx' in R:
install.packages('gamlssx', repos = c('https://paulnorthrop.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/paulnorthrop/gamlssx/issues

Datasets:
  • fremantle - Annual Maximum Sea Levels at Fremantle, Western Australia

On CRAN:

extreme-value-statisticsextremesgeneralized-additive-modelsregressionregression-analysis

3.90 score 2 stars 3 scripts 171 downloads 14 exports 9 dependencies

Last updated 4 months agofrom:8bb6955569. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winOKNov 13 2024
R-4.5-linuxOKNov 13 2024
R-4.4-winOKNov 13 2024
R-4.4-macOKNov 13 2024
R-4.3-winOKNov 13 2024
R-4.3-macOKNov 13 2024

Exports:dGEVfitGEVgev11egev12egev13egev22egev23egev33egevExpInfoGEVfisherGEVquasipGEVqGEVrGEV

Dependencies:gamlssgamlss.datagamlss.distlatticeMASSMatrixnievenlmesurvival