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mixAK (version 3.6-1)

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

3.6-1

License

GPL (>= 3)

Maintainer

Arnošt Komárek

Last Published

August 6th, 2014

Functions in mixAK (3.6-1)

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

Automatic layout for several plots in one figure

Acidity index of lakes in North-Central Wisconsin

GLMM_MCMCprior.b

Handle prior.eps argument of GLMM_MCMC function

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

Sample a pair (with replacement)

Truncated multivariate normal distribution

Multivariate normal distribution

Discriminant analysis for longitudinal profiles based on fitted GLMM's

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

GLMM_MCMCinit.alpha

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

rRotationMatrix

Random rotation matrix

NMixChainsDerived

Create MCMC chains derived from previously sampled values

Velocities of distant galaxies

Multivariate Student t distribution

Discriminant analysis based on MCMC output from the mixture model

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

NMixPredDensJoint2

Pairwise bivariate predictive density

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

Square root of a matrix

Subset of Mayo Clinic Primary Biliary Cirrhosis data

Mayo Clinic Primary Biliary Cirrhosis, sequential data

Dirichlet distribution

Initial (RE)ML fits for the GLMM_MCMC function

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

plot.NMixPlugDensJoint2

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

Old Faithful Geyser Data

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

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

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

Moore-Penrose pseudoinverse of a squared matrix

Data manipulation for the NMixMCMC function

Initial component allocations for the NMixMCMC function

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function

NMixPredCondDensMarg

Univariate conditional predictive density

plot.NMixPredDensMarg

Plot computed marginal predictive densities

Traceplots for selected parameters

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

Enzymatic activity in the blood

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

EM algorithm for a homoscedastic normal mixture

Data manipulation for the GLMM_MCMC function

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

plot.NMixPlugCondDensMarg

Plot computed univariate conditional densities (plug-in estimate)

Mixture of (multivariate) normal distributions

Truncated normal distribution

Posterior summary statistics for a difference of two quantities

Individual longitudinal profiles of a given variable

plot.NMixPredCDFMarg

Plot computed marginal predictive cumulative distribution functions

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

Signal Tandmobiel data

NMixPredDensMarg

Marginal (univariate) predictive density

Chains for mixture parameters

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities

Plot a function together with its confidence/credible bands

Simulated dataset

plot.NMixPlugCondDensJoint2

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

Wishart distribution

Plot individual longitudinal profiles

GLMM_MCMCinit.b

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

Initial values of censored observations for the NMixMCMC function

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

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

Summary for the mixture components

Re-labeling the MCMC output of the mixture model

GLMM_MCMCinit.eps

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

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

Signal Tandmobiel data - emergence times

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

generatePermutations

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

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities