gamlss: Generalised Additive Models for Location Scale and Shape

Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.

Version: 5.1-2
Depends: R (≥ 3.3.0), graphics, stats, splines, utils, grDevices, (≥ 5.0-0), gamlss.dist (≥ 4.3.1), nlme, parallel
Imports: MASS, survival, methods
Published: 2018-10-06
Author: Mikis Stasinopoulos [aut, cre, cph], Bob Rigby [aut], Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb]
Maintainer: Mikis Stasinopoulos <d.stasinopoulos at>
License: GPL-2 | GPL-3
NeedsCompilation: yes
Citation: gamlss citation info
Materials: README
In views: Econometrics
CRAN checks: gamlss results


Reference manual: gamlss.pdf
Package source: gamlss_5.1-2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: gamlss_5.1-2.tgz, r-oldrel: gamlss_5.1-2.tgz
Old sources: gamlss archive

Reverse dependencies:

Reverse depends: acid, binequality, BSagri, chicane, gamlss.add, gamlss.cens, gamlss.countKinf, gamlss.inf,,, gamlss.spatial,, gamlss.util, ImputeRobust, semsfa, ZIBseq
Reverse imports: AGD, childsds, distreg.vis, gamlssbssn
Reverse suggests: auditor, bamlss, broom, broom.mixed, depmixS4, ensemblepp, gamboostLSS, hnp, mice, mlt.docreg, MNM, PerformanceAnalytics, surveillance, tscount
Reverse enhances: texreg


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