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mixAK (version 5.3)

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

605

Version

5.3

License

GPL (>= 3)

Maintainer

Arnošt Komárek

Last Published

June 2nd, 2020

Functions in mixAK (5.3)

Data manipulation for the GLMM_MCMC function

Dirichlet distribution

GLMM_MCMCinit.alpha

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

Acidity index of lakes in North-Central Wisconsin

GLMM_MCMCprior.alpha

Handle prior.alpha argument of GLMM_MCMC function

Old Faithful Geyser Data

Enzymatic activity in the blood

Initial (RE)ML fits for the GLMM_MCMC function

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

GLMM_MCMCprior.eps

Handle prior.eps argument of GLMM_MCMC function

GLMM_MCMCinit.b

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

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

GLMM_MCMCscale.b

Handle scale.b argument of GLMM_MCMC function

GLMM_MCMCinit.eps

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

GLMM_MCMCwrapper

Wrapper to the GLMM_MCMC main simulation.

Discriminant analysis for longitudinal profiles based on fitted GLMM's

Clustering based on the MCMC output of the mixture model

Discriminant analysis for longitudinal profiles based on fitted GLMM's

EM algorithm for a homoscedastic normal mixture

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

NMixChainsDerived

Create MCMC chains derived from previously sampled values

Multivariate normal distribution

NMixPlugCondDensMarg

Univariate conditional densities: plug-in estimate

Mixture of (multivariate) normal distributions

Data manipulation for the NMixMCMC function

Moore-Penrose pseudoinverse of a squared matrix

Initial values of censored observations for the NMixMCMC function

NMixPlugCondDensJoint2

Pairwise bivariate conditional densities: plug-in estimate

Multivariate Student t distribution

NMixPlugDensMarg

Marginal (univariate) densities: plug-in estimate

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

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

Initial component allocations for the NMixMCMC function

Automatic layout for several plots in one figure

Re-labeling the MCMC output of the mixture model

NMixPlugDensJoint2

Pairwise bivariate densities: plug-in estimate

fitted.GLMM_MCMC

Fitted profiles in the GLMM model

NMixMCMCwrapper

Wrapper to the NMixMCMC main simulation.

Signal Tandmobiel data

Signal Tandmobiel data - emergence times

NMixPredCDFMarg

Marginal (univariate) predictive cumulative distribution function

Velocities of distant galaxies

NMixPredCondCDFMarg

Univariate conditional predictive cumulative distribution function

Truncated multivariate normal distribution

Chains for mixture parameters

generatePermutations

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

NMixPredDensMarg

Marginal (univariate) predictive density

NMixPredDensJoint2

Pairwise bivariate predictive density

Square root of a matrix

Subset of Mayo Clinic Primary Biliary Cirrhosis data

Truncated normal distribution

NMixPredCondDensMarg

Univariate conditional predictive density

Sample a pair (with replacement)

NMixRelabelAlgorithm

Argument manipulation for the NMixRelabel functions

Summary for the mixture components

rRotationMatrix

Random rotation matrix

Mayo Clinic Primary Biliary Cirrhosis, sequential data

plot.NMixPlugDensJoint2

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

NMixPredCondDensJoint2

Pairwise bivariate conditional predictive densities

Wishart distribution

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

plot.NMixPlugCondDensMarg

Plot computed univariate conditional densities (plug-in estimate)

plot.NMixPredDensMarg

Plot computed marginal predictive densities

Discriminant analysis based on MCMC output from the mixture model

plot.NMixPlugDensMarg

Plot computed marginal predictive densities

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

Plot a function together with its confidence/credible bands

Plot individual longitudinal profiles

plot.NMixPredCDFMarg

Plot computed marginal predictive cumulative distribution functions

plot.NMixPredCondDensMarg

Plot computed univariate conditional predictive densities

Individual longitudinal profiles of a given variable

plot.NMixPredCondDensJoint2

Plot computed predictive pairwise bivariate conditional densities

plot.NMixPredCondCDFMarg

Plot computed univariate conditional predictive cumulative distribution functions

plot.NMixPredDensJoint2

Plot computed marginal pairwise bivariate predictive densities

Simulated dataset

Posterior summary statistics for a difference of two quantities

plot.NMixPlugCondDensJoint2

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

Traceplots for selected parameters