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mixAK (version 4.2)

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

4.2

License

GPL (>= 3)

Maintainer

Arnošt Komárek

Last Published

August 2nd, 2015

Functions in mixAK (4.2)

Square root of a matrix

Multivariate Student t distribution

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Discriminant analysis for longitudinal profiles based on fitted GLMM's

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

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

Multivariate normal distribution

plot.NMixPlugCondDensJoint2

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

Mixture of (multivariate) normal distributions

plot.NMixPredCDFMarg

Plot computed marginal predictive cumulative distribution functions

Moore-Penrose pseudoinverse of a squared matrix

Initial component allocations for the NMixMCMC function

Subset of Mayo Clinic Primary Biliary Cirrhosis data

plot.NMixPlugDensJoint2

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

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

Chains for mixture parameters

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

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

Re-labeling the MCMC output of the mixture model

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

Clustering based on the MCMC output of the mixture model

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

NMixPredDensJoint2

Pairwise bivariate predictive density

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

Data manipulation for the NMixMCMC function

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

Simulated dataset

Mayo Clinic Primary Biliary Cirrhosis, sequential data

GLMM_MCMCprior.b

Handle prior.eps argument of GLMM_MCMC function

Sample a pair (with replacement)

rRotationMatrix

Random rotation matrix

plot.NMixPredDensMarg

Plot computed marginal predictive densities

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

Truncated normal distribution

Signal Tandmobiel data - emergence times

generatePermutations

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

GLMM_MCMCinit.eps

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

GLMM_MCMCinit.b

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

Enzymatic activity in the blood

Traceplots for selected parameters

Automatic layout for several plots in one figure

Initial (RE)ML fits for the GLMM_MCMC function

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

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities

Summary for the mixture components

NMixPredCondDensMarg

Univariate conditional predictive density

EM algorithm for a homoscedastic normal mixture

Plot a function together with its confidence/credible bands

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

Individual longitudinal profiles of a given variable

Dirichlet distribution

Old Faithful Geyser Data

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

Posterior summary statistics for a difference of two quantities

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

Initial values of censored observations for the NMixMCMC function

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

Discriminant analysis based on MCMC output from the mixture model

NMixPredDensMarg

Marginal (univariate) predictive density

plot.NMixPlugCondDensMarg

Plot computed univariate conditional densities (plug-in estimate)

NMixChainsDerived

Create MCMC chains derived from previously sampled values

Acidity index of lakes in North-Central Wisconsin

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

Wishart distribution

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities

Signal Tandmobiel data

GLMM_MCMCinit.alpha

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

Velocities of distant galaxies

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

Data manipulation for the GLMM_MCMC function

Plot individual longitudinal profiles

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

Truncated multivariate normal distribution

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function