PReMiuM: Dirichlet Process Bayesian Clustering, Profile Regression
Version 3.1.4

Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection.

Browse man pages Browse package API and functions Browse package files

AuthorDavid I. Hastie <david.hastie@rsimony.com>, Silvia Liverani <liveranis@gmail.com> and Sylvia Richardson <sylvia.richardson@mrc-bsu.cam.ac.uk> with contributions from Aurore J. Lavigne, Lucy Leigh, Lamiae Azizi
Date of publication2016-12-28 18:03:52
MaintainerSilvia Liverani <liveranis@gmail.com>
LicenseGPL-2
Version3.1.4
URL http://www.silvialiverani.com/software/
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("PReMiuM")

Man pages

calcAvgRiskAndProfile: Calculation of the average risks and profiles
calcDissimilarityMatrix: Calculates the dissimilarity matrix
calcOptimalClustering: Calculation of the optimal clustering
calcPredictions: Calculates the predictions
clusSummaryBernoulliDiscrete: Sample datasets for profile regression
computeRatioOfVariance: computeRatioOfVariance
generateSampleDataFile: Generate sample data files for profile regression
globalParsTrace: Plot of the trace of some of the global parameters
heatDissMat: Plot the heatmap of the dissimilarity matrix
is.wholenumber: Function to check if a number is a whole number
mapforGeneratedData: Map generated data
margModelPosterior: Marginal Model Posterior
plotPredictions: Plot the conditional density using the predicted scenarios
plotRiskProfile: Plot the Risk Profiles
PReMiuM-package: Dirichlet Process Bayesian Clustering
profRegr: Profile Regression
setHyperparams: Definition of characteristics of sample datasets for profile...
summariseVarSelectRho: summariseVarSelectRho
vec2mat: Vector to upper triangular matrix

Functions

PReMiuM Man page
PReMiuMpackage Man page
calcAvgRiskAndProfile Man page Source code
calcDissimilarityMatrix Man page Source code
calcOptimalClustering Man page Source code
calcPredictions Man page Source code
clusSummaryBernoulliDiscrete Man page Source code
clusSummaryBernoulliDiscreteSmall Man page Source code
clusSummaryBernoulliMixed Man page Source code
clusSummaryBernoulliNormal Man page Source code
clusSummaryBinomialNormal Man page Source code
clusSummaryCategoricalDiscrete Man page Source code
clusSummaryNormalDiscrete Man page Source code
clusSummaryNormalNormal Man page Source code
clusSummaryNormalNormalSpatial Man page Source code
clusSummaryPoissonDiscrete Man page Source code
clusSummaryPoissonNormal Man page Source code
clusSummaryPoissonNormalSpatial Man page Source code
clusSummaryQuantileNormal Man page Source code
clusSummaryVarSelectBernoulliDiscrete Man page Source code
clusSummaryWeibullDiscrete Man page Source code
color.scale Source code
computeRatioOfVariance Man page Source code
cs.draw Source code
generateSampleDataFile Man page Source code
globalParsTrace Man page Source code
heatDissMat Man page Source code
is.wholenumber Man page Source code
mapforGeneratedData Man page Source code
margModelPosterior Man page Source code
pYGivenZW_Bernoulli Source code
pYGivenZW_Bernoulli_gradient Source code
pYGivenZW_Bernoulli_hessianMat Source code
pZpXpY Source code
plotPredictions Man page Source code
plotRiskProfile Man page Source code
prec_Matrix Source code
profRegr Man page Source code
setHyperparams Man page Source code
summariseVarSelectRho Man page Source code
vec2mat Man page Source code
write_neigh Source code

Files

inst
inst/CITATION
src
src/Makevars
src/postProcess.cpp
src/PReMiuM.cpp
src/Makevars.win
src/include
src/include/postProcess.h
src/include/PReMiuMData.h
src/include/PReMiuMOptions.h
src/include/PReMiuMArs.h
src/include/PReMiuMModel.h
src/include/PReMiuMProposals.h
src/include/MCMC
src/include/MCMC/model.h
src/include/MCMC/chain.h
src/include/MCMC/state.h
src/include/MCMC/proposal.h
src/include/MCMC/sampler.h
src/include/PReMiuMArs.cpp
src/include/PReMiuMIO.h
src/include/Math
src/include/Math/random.h
src/include/Math/Error.h
src/include/Math/ars2.h
src/include/Math/mathfunctions.h
src/include/Math/distribution.h
NAMESPACE
R
R/postProcess.R
R/generateData.R
MD5
DESCRIPTION
ChangeLog
man
man/computeRatioOfVariance.Rd
man/vec2mat.Rd
man/setHyperparams.Rd
man/margModelPosterior.Rd
man/globalParsTrace.Rd
man/PReMiuM-package.Rd
man/is.wholenumber.Rd
man/clusSummaryBernoulliDiscrete.Rd
man/calcAvgRiskAndProfile.Rd
man/mapforGeneratedData.Rd
man/plotPredictions.Rd
man/heatDissMat.Rd
man/generateSampleDataFile.Rd
man/calcOptimalClustering.Rd
man/calcDissimilarityMatrix.Rd
man/profRegr.Rd
man/calcPredictions.Rd
man/plotRiskProfile.Rd
man/summariseVarSelectRho.Rd
PReMiuM documentation built on May 20, 2017, 5:31 a.m.