gamlss.dist: Distributions for Generalized Additive Models for Location Scale and Shape

A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a ”log” or a ”logit' transformation respectively.

Version: 5.1-7
Depends: R (≥ 2.15.0), MASS, graphics, stats, methods, grDevices
Published: 2020-07-13
Author: Mikis Stasinopoulos [aut, cre, cph], Robert Rigby [aut], Calliope Akantziliotou [ctb], Vlasios Voudouris [ctb], Gillian Heller [ctb], Fernanda De Bastiani [ctb], Raydonal Ospina [ctb], Nicoletta Motpan [ctb], Fiona McElduff [ctb], Majid Djennad [ctb], Marco Enea [ctb], Alexios Ghalanos [ctb], Christos Argyropoulos [ctb], Almond Stocker [ctb], Jens Lichter [ctb], Stanislaus Stadlmann [ctb]
Maintainer: Mikis Stasinopoulos <d.stasinopoulos at londonmet.ac.uk>
License: GPL-2 | GPL-3
URL: http://www.gamlss.org/
NeedsCompilation: yes
In views: Distributions
CRAN checks: gamlss.dist results

Downloads:

Reference manual: gamlss.dist.pdf
Package source: gamlss.dist_5.1-7.tar.gz
Windows binaries: r-devel: gamlss.dist_5.1-7.zip, r-release: gamlss.dist_5.1-7.zip, r-oldrel: gamlss.dist_5.1-7.zip
macOS binaries: r-release: gamlss.dist_5.1-7.tgz, r-oldrel: gamlss.dist_5.1-7.tgz
Old sources: gamlss.dist archive

Reverse dependencies:

Reverse depends: acid, binequality, gamlss, gamlss.add, gamlss.cens, gamlss.countKinf, gamlss.demo, gamlss.inf, gamlss.mx, gamlss.spatial, gamlss.tr, gamlss.util, gamlssbssn
Reverse imports: AGD, asymmetry.measures, childsds, distreg.vis, GJRM, ImputeRobust, list, powdist, PReMiuM, QFASA, rpql, Wrapped, ZIBseq
Reverse suggests: betaboost, broom, coveffectsplot, depmixS4, EstimationTools, fitdistrplus, gamboostLSS, hnp, mazeinda, PerformanceAnalytics

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