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mixAK (version 3.4)

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

3.4

License

GPL (>= 3)

Maintainer

Arnošt Komárek

Last Published

August 5th, 2013

Functions in mixAK (3.4)

Data manipulation for the GLMM_MCMC function

Enzymatic activity in the blood

Initial (RE)ML fits for the GLMM_MCMC function

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

EM algorithm for a homoscedastic normal mixture

Chains for mixture parameters

Data manipulation for the NMixMCMC function

Mixture of (multivariate) normal distributions

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function

Wishart distribution

Square root of a matrix

Truncated multivariate normal distribution

Dirichlet distribution

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

Traceplots for selected parameters

Sample a pair (with replacement)

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

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

plot.NMixPredDensMarg

Plot computed marginal predictive densities

Moore-Penrose pseudoinverse of a squared matrix

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

Signal Tandmobiel data

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities

NMixPredCondDensMarg

Univariate conditional predictive density

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Plot individual longitudinal profiles

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

Acidity index of lakes in North-Central Wisconsin

GLMM_MCMCinit.alpha

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

Re-labeling the MCMC output of the mixture model

Simulated dataset

Multivariate normal distribution

Summary for the mixture components

Initial component allocations for the NMixMCMC function

Plot a function together with its confidence/credible bands

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

Mayo Clinic Primary Biliary Cirrhosis, sequential data

NMixChainsDerived

Create MCMC chains derived from previously sampled values

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

GLMM_MCMCinit.b

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

Velocities of distant galaxies

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

Discriminant analysis based on MCMC output from the mixture model

plot.NMixPlugCondDensJoint2

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

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

Multivariate Student t distribution

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

Subset of Mayo Clinic Primary Biliary Cirrhosis data

NMixPredDensMarg

Marginal (univariate) predictive density

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

Automatic layout for several plots in one figure

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

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

Initial values of censored observations for the NMixMCMC function

NMixPredDensJoint2

Pairwise bivariate predictive density

Signal Tandmobiel data - emergence times

GLMM_MCMCinit.eps

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

Old Faithful Geyser Data

GLMM_MCMCprior.b

Handle prior.eps argument of GLMM_MCMC function

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

generatePermutations

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

Individual longitudinal profiles of a given variable

Truncated normal distribution

Posterior summary statistics for a difference of two quantities

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

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

plot.NMixPredCDFMarg

Plot computed marginal predictive cumulative distribution functions

rRotationMatrix

Random rotation matrix

plot.NMixPlugCondDensMarg

Plot computed univariate conditional densities (plug-in estimate)

plot.NMixPlugDensJoint2

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