Package: gamlssx 1.0.2

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_1.0.2.tar.gz
gamlssx_1.0.2.zip(r-4.7)gamlssx_1.0.2.zip(r-4.6)gamlssx_1.0.2.zip(r-4.5)
gamlssx_1.0.2.tgz(r-4.6-any)gamlssx_1.0.2.tgz(r-4.5-any)
gamlssx_1.0.2.tar.gz(r-4.7-any)gamlssx_1.0.2.tar.gz(r-4.6-any)
gamlssx_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gamlssx/json (API)
NEWS

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

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

Pkgdown/docs site:https://paulnorthrop.github.io

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

On CRAN:

Conda:

extreme-value-statisticsextremesgeneralized-additive-modelsregressionregression-analysis

3.65 score 3 stars 1 packages 6 scripts 188 downloads 14 exports 9 dependencies

Last updated from:87ebd8bb67. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK128
source / vignettesOK147
linux-release-x86_64OK121
macos-release-arm64OK89
macos-oldrel-arm64OK88
windows-develOK86
windows-releaseOK92
windows-oldrelOK114
wasm-releaseOK91

Exports:dGEVfitGEVgev11egev12egev13egev22egev23egev33egevExpInfoGEVfisherGEVquasipGEVqGEVrGEV

Dependencies:gamlssgamlss.datagamlss.distlatticeMASSMatrixnievenlmesurvival