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mixAK (version 3.10)

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

Description

This package 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.

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Version

Install

install.packages('mixAK')

Monthly Downloads

326

Version

3.10

License

GPL (>= 3)

Maintainer

Arnošt Komárek

Last Published

February 6th, 2015

Functions in mixAK (3.10)

GLMM_MCMCprior.b

Handle prior.eps argument of GLMM_MCMC function

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

NMixPredCondDensMarg

Univariate conditional predictive density

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

Dirichlet distribution

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

NMixPredDensJoint2

Pairwise bivariate predictive density

Subset of Mayo Clinic Primary Biliary Cirrhosis data

Data manipulation for the GLMM_MCMC function

Clustering based on the MCMC output of the mixture model

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

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

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

Enzymatic activity in the blood

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

GLMM_MCMCinit.alpha

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

Sample a pair (with replacement)

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

Initial component allocations for the NMixMCMC function

Mayo Clinic Primary Biliary Cirrhosis, sequential data

plot.NMixPredDensMarg

Plot computed marginal predictive densities

Summary for the mixture components

Automatic layout for several plots in one figure

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities

Initial (RE)ML fits for the GLMM_MCMC function

Posterior summary statistics for a difference of two quantities

Wishart distribution

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

NMixChainsDerived

Create MCMC chains derived from previously sampled values

Simulated dataset

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

rRotationMatrix

Random rotation matrix

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

Plot individual longitudinal profiles

plot.NMixPlugCondDensJoint2

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

Multivariate Student t distribution

Traceplots for selected parameters

Square root of a matrix

Re-labeling the MCMC output of the mixture model

Discriminant analysis based on MCMC output from the mixture model

Plot a function together with its confidence/credible bands

Signal Tandmobiel data

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

plot.NMixPlugCondDensMarg

Plot computed univariate conditional densities (plug-in estimate)

plot.NMixPredCDFMarg

Plot computed marginal predictive cumulative distribution functions

plot.NMixPlugDensJoint2

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

Acidity index of lakes in North-Central Wisconsin

GLMM_MCMCinit.b

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

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Chains for mixture parameters

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

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities

Individual longitudinal profiles of a given variable

Multivariate normal distribution

Mixture of (multivariate) normal distributions

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

Moore-Penrose pseudoinverse of a squared matrix

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

Data manipulation for the NMixMCMC function

EM algorithm for a homoscedastic normal mixture

Truncated normal distribution

Initial values of censored observations for the NMixMCMC function

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

Truncated multivariate normal distribution

Signal Tandmobiel data - emergence times

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

GLMM_MCMCinit.eps

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

Velocities of distant galaxies

Old Faithful Geyser Data

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function

NMixPredDensMarg

Marginal (univariate) predictive density

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

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

generatePermutations

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