gamlss: Generalized 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:
5.5-0
Published:
2025年08月19日
Author:
Mikis Stasinopoulos
ORCID iD [aut, cre,
cph],
Robert Rigby
ORCID iD
[aut],
Vlasios Voudouris [ctb],
Calliope Akantziliotou [ctb],
Marco Enea [ctb],
Daniil Kiose
ORCID iD
[ctb],
Achim Zeileis
ORCID iD
[ctb]
Maintainer:
Mikis Stasinopoulos <d.stasinopoulos at gre.ac.uk>
NeedsCompilation:
yes
Documentation:
Downloads:
Reverse dependencies:
Reverse depends:
acid,
binequality,
BSagri,
chicane,
gamlss.add,
gamlss.cens,
gamlss.foreach,
gamlss.ggplots,
gamlss.inf,
gamlss.lasso,
gamlss.mx,
gamlss.tr,
ImputeRobust,
metamicrobiomeR,
semsfa
Reverse imports:
AGD,
bodycompref,
borealis,
childsds,
circhelp,
ComBatFamQC,
DEsingle,
DiscreteDists,
distreg.vis,
dsBase,
fMRIscrub,
gamlssbssn,
gamlssx,
hytest,
JWileymisc,
mixpoissonreg,
normref,
OutSeekR,
pbox,
QFASA,
RelDists,
scDesign3,
scLANE,
scRecover,
SEI,
SelectBoost.beta,
shinyCLT,
spatemR,
SPIChanges,
sregsurvey,
SVEMnet,
ugomquantreg,
vasicekreg
Reverse suggests:
bamlss,
broom.mixed,
depmixS4,
ensemblepp,
gamboostLSS,
ggeffects,
hnp,
insight,
linkSet,
marginaleffects,
MNM,
modelsummary,
parameters,
PerformanceAnalytics,
qra,
ramr,
surveillance,
tram
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