flexmix: Flexible Mixture Modeling
A general framework for finite mixtures of regression
models using the EM algorithm is implemented. The E-step and all
data handling are provided, while the M-step can be supplied by the
user to easily define new models. Existing drivers implement
mixtures of standard linear models, generalized linear models and
model-based clustering.
Version:
2.3-20
Imports:
graphics, grid, grDevices, methods,
modeltools (≥ 0.2-16),
nnet, stats, stats4, utils
Suggests:
actuar,
codetools,
diptest,
Ecdat,
ellipse,
gclus,
glmnet,
lme4 (≥ 1.1),
MASS,
mgcv (≥ 1.8-0),
mlbench,
multcomp,
mvtnorm,
SuppDists,
survival
Published:
2025年02月28日
Author:
Bettina Gruen
ORCID iD
[aut, cre],
Friedrich Leisch
ORCID iD
[aut],
Deepayan Sarkar
ORCID iD
[ctb],
Frederic Mortier [ctb],
Nicolas Picard
ORCID iD
[ctb]
Maintainer:
Bettina Gruen <Bettina.Gruen at R-project.org>
NeedsCompilation:
no
Documentation:
Downloads:
Reverse dependencies:
Reverse imports:
betareg,
circlus,
CONFESS,
CytoGLMM,
distributionsrd,
flexord,
fmerPack,
fpc,
hyreg2,
longmixr,
Mercator,
miQC,
plotmm,
RobMixReg,
sBIC,
scPipe,
trajmsm
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