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mixAK (version 3.1)

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

3.1

License

GPL (>= 2)

Maintainer

Arnošt Komárek

Last Published

June 11th, 2013

Functions in mixAK (3.1)

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

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

NMixChainsDerived

Create MCMC chains derived from previously sampled values

Multivariate normal distribution

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Initial values of censored observations for the NMixMCMC function

GLMM_MCMCinit.eps

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

Subset of Mayo Clinic Primary Biliary Cirrhosis data

NMixPredDensJoint2

Pairwise bivariate predictive density

NMixPredCondDensMarg

Univariate conditional predictive density

Velocities of distant galaxies

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities

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

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

Discriminant analysis based on MCMC output from the mixture model

Truncated normal distribution

Signal Tandmobiel data

GLMM_MCMCprior.b

Handle prior.eps argument of GLMM_MCMC function

generatePermutations

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

plot.NMixPlugDensJoint2

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

Chains for mixture parameters

plot.NMixPlugCondDensMarg

Plot computed univariate conditional densities (plug-in estimate)

Automatic layout for several plots in one figure

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function

Posterior summary statistics for a difference of two quantities

Initial component allocations for the NMixMCMC function

EM algorithm for a homoscedastic normal mixture

Individual longitudinal profiles of a given variable

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

Acidity index of lakes in North-Central Wisconsin

Dirichlet distribution

Traceplots for selected parameters

Mixture of (multivariate) normal distributions

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

NMixPredDensMarg

Marginal (univariate) predictive density

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

Simulated dataset

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

Moore-Penrose pseudoinverse of a squared matrix

Data manipulation for the GLMM_MCMC function

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

GLMM_MCMCinit.b

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

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

Clustering based on the MCMC output of the mixture model

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

Wishart distribution

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

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

Multivariate Student t distribution

Old Faithful Geyser Data

plot.NMixPlugCondDensJoint2

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

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

Signal Tandmobiel data - emergence times

Plot a function together with its confidence/credible bands

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

GLMM_MCMCinit.alpha

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

rRotationMatrix

Random rotation matrix

Truncated multivariate normal distribution

Data manipulation for the NMixMCMC function

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

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

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

Enzymatic activity in the blood

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities

Square root of a matrix

Mayo Clinic Primary Biliary Cirrhosis, sequential data

Re-labeling the MCMC output of the mixture model

Summary for the mixture components

Plot individual longitudinal profiles

plot.NMixPredDensMarg

Plot computed marginal predictive densities

plot.NMixPredCDFMarg

Plot computed marginal predictive cumulative distribution functions

Sample a pair (with replacement)

Initial (RE)ML fits for the GLMM_MCMC function