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), . The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.

Those are the function for creating the package gamlss


Reference manual

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5.3-4 by Mikis Stasinopoulos, 10 months ago

Browse source code at

Authors: Mikis Stasinopoulos [aut, cre, cph] , Bob Rigby [aut] , Vlasios Voudouris [ctb] , Calliope Akantziliotou [ctb] , Marco Enea [ctb] , Daniil Kiose [ctb]

Documentation:   PDF Manual  

Task views: Econometrics

GPL-2 | GPL-3 license

Imports MASS, survival, methods

Depends on graphics, stats, splines, utils, grDevices,, gamlss.dist, nlme, parallel

Imported by AGD, BPmodel, QFASA, childsds, distreg.vis, gamlssbssn, mixpoissonreg, sregsurvey, ugomquantreg, vasicekreg.

Depended on by BSagri, ImputeRobust, ZIBseq, acid, binequality, chicane, gamlss.add, gamlss.cens, gamlss.countKinf, gamlss.foreach, gamlss.inf, gamlss.lasso,,, gamlss.spatial,, metamicrobiomeR, semsfa.

Suggested by MNM, PerformanceAnalytics, bamlss, broom.mixed, depmixS4, ensemblepp, gamboostLSS, ggeffects, hnp, insight, mlt.docreg, modelsummary, parameters, qra, surveillance.

Enhanced by MuMIn, texreg.

See at CRAN