CRAN/E | flexmix

flexmix

Flexible Mixture Modeling

Installation

About

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.

Citation flexmix citation info

Key Metrics

Version 2.3-19
R ≥ 2.15.0
Published 2023-03-16 407 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks flexmix results

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Maintainer

Maintainer

Bettina Gruen

Bettina.Gruen@R-project.org

Authors

Bettina Gruen

aut / cre

Friedrich Leisch

aut

Deepayan Sarkar

ctb

Frederic Mortier

ctb

Nicolas Picard

ctb

Material

NEWS
Reference manual
Package source

In Views

Cluster
Environmetrics
Psychometrics

Vignettes

Finite Mixture Model Diagnostics Using Resampling Methods
FlexMix: A General Framework for Finite Mixture Models and Latent Class Regression in R
FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters
Applications of finite mixtures of regression models

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

flexmix archive

Depends

R ≥ 2.15.0
lattice

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

Reverse Depends

evaluomeR
flexmixNL
MAP
MAZE
psychomix
scde

Reverse Imports

betareg
CONFESS
CytoGLMM
distributionsrd
fmerPack
fpc
GOSim
longmixr
lpme
Mercator
miQC
RobMixReg
sBIC
scPipe

Reverse Suggests

catdata
HSAUR
HSAUR2
HSAUR3
latrend
morpheus
movMF
plotmm
rexposome
starvz

Reverse Enhances

clue