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

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Reference manual

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install.packages("gamlss")

5.1-4 by Mikis Stasinopoulos, 4 months ago


http://www.gamlss.org/


Browse source code at https://github.com/cran/gamlss


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.data, gamlss.dist, nlme, parallel


Imported by AGD, QFASA, childsds, distreg.vis, gamlssbssn.

Depended on by BSagri, ImputeRobust, ZIBseq, acid, binequality, chicane, gamlss.add, gamlss.cens, gamlss.countKinf, gamlss.inf, gamlss.mx, gamlss.nl, gamlss.spatial, gamlss.tr, gamlss.util, metamicrobiomeR, semsfa.

Suggested by MNM, PerformanceAnalytics, bamlss, broom, broom.mixed, depmixS4, ensemblepp, gamboostLSS, hnp, insight, mice, mlt.docreg, surveillance, tscount.

Enhanced by texreg.


See at CRAN