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mixAK (version 5.8)

Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering

Description

Contains a mixture of statistical methods including the MCMC methods to analyze normal mixtures. Additionally, model based clustering methods are implemented to perform classification based on (multivariate) longitudinal (or otherwise correlated) data. The basis for such clustering is a mixture of multivariate generalized linear mixed models. The package is primarily related to the publications Komárek (2009, Comp. Stat. and Data Anal.) and Komárek and Komárková (2014, J. of Stat. Soft.) . It also implements methods published in Komárek and Komárková (2013, Ann. of Appl. Stat.) , Hughes, Komárek, Bonnett, Czanner, García-Fiñana (2017, Stat. in Med.) , Jaspers, Komárek, Aerts (2018, Biom. J.) and Hughes, Komárek, Czanner, García-Fiñana (2018, Stat. Meth. in Med. Res) .

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Version

Install

install.packages('mixAK')

Monthly Downloads

1,211

Version

5.8

License

GPL (>= 3)

Maintainer

Arnošt Komárek

Last Published

September 16th, 2024

Functions in mixAK (5.8)

Old Faithful Geyser Data

Dirichlet distribution

GLMM_MCMCinit.alpha

Handle init.alpha or init2.alpha argument of GLMM_MCMC function

Initial (RE)ML fits for the GLMM_MCMC function

Data manipulation for the GLMM_MCMC function

Best linear approximation with respect to the mean square error (theoretical linear regression).

Enzymatic activity in the blood

MCMC estimation of a (multivariate) generalized linear mixed model with a normal mixture in the distribution of random effects

GLMM_MCMCinit.eps

Handle init.eps or init2.eps argument of GLMM_MCMC function

GLMM_MCMCprior.b

Handle prior.eps argument of GLMM_MCMC function

Acidity index of lakes in North-Central Wisconsin

GLMM_MCMCinit.b

Handle init.b or init2.b argument of GLMM_MCMC function

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Velocities of distant galaxies

EM algorithm for a homoscedastic normal mixture

Multivariate Student t distribution

NMixChainsDerived

Create MCMC chains derived from previously sampled values

Clustering based on the MCMC output of the mixture model

Multivariate normal distribution

Moore-Penrose pseudoinverse of a squared matrix

Square root of a matrix

Mixture of (multivariate) normal distributions

Chains for mixture parameters

MCMC estimation of (multivariate) normal mixtures with possibly censored data.

Initial component allocations for the NMixMCMC function

Data manipulation for the NMixMCMC function

Discriminant analysis based on plug-in estimates from the mixture model

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

Initial values of censored observations for the NMixMCMC function

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

Pseudo goodness-of-fit test for a normal mixture model

NMixPredCondDensMarg

Univariate conditional predictive density

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

Discriminant analysis based on MCMC output from the mixture model

NMixPredDensMarg

Marginal (univariate) predictive density

Re-labeling the MCMC output of the mixture model

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

Summary for the mixture components

Truncated multivariate normal distribution

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

NMixPredDensJoint2

Pairwise bivariate predictive density

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function

Truncated normal distribution

Wishart distribution

Subset of Mayo Clinic Primary Biliary Cholangitis (Cirrhosis) data

Individual longitudinal profiles of a given variable

Signal Tandmobiel data

Transform fitted distribution of Y=trans(T) into distribution of T

Conversion of a symmetric matrix stored in a packed format (lower triangle only) into a matrix

Signal Tandmobiel data - emergence times

Posterior summary statistics for a difference of two quantities

Mayo Clinic Primary Biliary Cholangitis (Cirrhosis), sequential data

Traceplots for selected parameters

plot.NMixPlugCondDensMarg

Plot computed univariate conditional densities (plug-in estimate)

plot.NMixPlugCondDensJoint2

Plot computed pairwise bivariate conditional densities (plug-in estimate)

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

generatePermutations

Generate all permutations of (1, ..., K)

plot.NMixPlugDensJoint2

Plot computed marginal pairwise bivariate densities (plug-in estimate)

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

plot.NMixPredCDFMarg

Plot computed marginal predictive cumulative distribution functions

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

Simulated dataset

rRotationMatrix

Random rotation matrix

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities

Sample a pair (with replacement)

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

Automatic layout for several plots in one figure

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities

Plot a function together with its confidence/credible bands

plot.NMixPredDensMarg

Plot computed marginal predictive densities

Plot individual longitudinal profiles