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mixAK (version 4.1-1)

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.

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Version

Install

install.packages('mixAK')

Monthly Downloads

326

Version

4.1-1

License

GPL (>= 3)

Maintainer

Arnošt Komárek

Last Published

July 28th, 2015

Functions in mixAK (4.1-1)

Acidity index of lakes in North-Central Wisconsin

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

Multivariate Student t distribution

Dirichlet distribution

Initial values of censored observations for the NMixMCMC function

Individual longitudinal profiles of a given variable

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

Chains for mixture parameters

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

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

Data manipulation for the NMixMCMC function

Data manipulation for the GLMM_MCMC function

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

Subset of Mayo Clinic Primary Biliary Cirrhosis data

Initial (RE)ML fits for the GLMM_MCMC function

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

plot.NMixPlugDensJoint2

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

Plot individual longitudinal profiles

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

GLMM_MCMCinit.eps

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

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

NMixPredDensJoint2

Pairwise bivariate predictive density

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities

Mayo Clinic Primary Biliary Cirrhosis, sequential data

Simulated dataset

GLMM_MCMCinit.alpha

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

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

Enzymatic activity in the blood

Automatic layout for several plots in one figure

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

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

GLMM_MCMCprior.b

Handle prior.eps argument of GLMM_MCMC function

rRotationMatrix

Random rotation matrix

Square root of a matrix

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Mixture of (multivariate) normal distributions

Moore-Penrose pseudoinverse of a squared matrix

Discriminant analysis based on MCMC output from the mixture model

NMixChainsDerived

Create MCMC chains derived from previously sampled values

Wishart distribution

EM algorithm for a homoscedastic normal mixture

Traceplots for selected parameters

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Signal Tandmobiel data - emergence times

Clustering based on the MCMC output of the mixture model

NMixPredCondDensMarg

Univariate conditional predictive density

NMixPredDensMarg

Marginal (univariate) predictive density

generatePermutations

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

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function

Sample a pair (with replacement)

plot.NMixPredDensMarg

Plot computed marginal predictive densities

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

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

Truncated multivariate normal distribution

Plot a function together with its confidence/credible bands

Posterior summary statistics for a difference of two quantities

Initial component allocations for the NMixMCMC function

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

Re-labeling the MCMC output of the mixture model

plot.NMixPlugCondDensJoint2

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

Multivariate normal distribution

Old Faithful Geyser Data

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

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

Signal Tandmobiel data

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

Truncated normal distribution

GLMM_MCMCinit.b

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

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

Velocities of distant galaxies

Summary for the mixture components

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities