CRAN/E | PReMiuM

PReMiuM

Dirichlet Process Bayesian Clustering, Profile Regression

Installation

About

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. The main reference for the package is Liverani, Hastie, Azizi, Papathomas and Richardson (2015) doi:10.18637/jss.v064.i07.

Citation PReMiuM citation info
www.silvialiverani.com/software/
System requirements GNU make

Key Metrics

Version 3.2.13
R ≥ 3.5.1
Published 2024-01-09 79 days ago
Needs compilation? yes
License GPL-2
CRAN checks PReMiuM results

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Maintainer

Maintainer

Silvia Liverani

liveranis@gmail.com

Authors

David I. Hastie
Silvia Liverani
Sylvia Richardson
Aurore J. Lavigne
Lucy Leigh
Lamiae Azizi
Xi Liu
Ruizhu Huang
Austin Gratton
Wei Jing

Material

ChangeLog
Reference manual
Package source

In Views

Bayesian
Cluster
MissingData
Spatial
Survival

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

PReMiuM archive

Depends

R ≥ 3.5.1

Imports

Rcpp ≥ 0.12.13
ggplot2 ≥ 2.2
cluster
plotrix ≥3.6-6
gamlss.dist ≥ 4.3-1
data.table ≥ 1.10.4-3
spdep ≥ 0.7-7
sf ≥ 1.0-8

Suggests

testthat ≥ 1.0.2

LinkingTo

Rcpp
RcppEigen ≥ 0.3.3.3.0
BH ≥ 1.65.0-1