predkmeans: Covariate Adaptive Clustering

Implements the predictive k-means method for clustering observations, using a mixture of experts model to allow covariates to influence cluster centers. Motivated by air pollution epidemiology settings, where cluster membership needs to be predicted across space. Includes functions for predicting cluster membership using spatial splines and principal component analysis (PCA) scores using either multinomial logistic regression or support vector machines (SVMs). For method details see Keller et al. (2017) <doi:10.1214/16-AOAS992>.

Version:	0.1.1
Imports:	Rcpp (≥ 0.11.5), maxLik, e1071, mgcv
LinkingTo:	Rcpp, RcppArmadillo
Published:	2019-12-16
DOI:	10.32614/CRAN.package.predkmeans
Author:	Joshua Keller
Maintainer:	Joshua Keller <joshua.keller at colostate.edu>
License:	GPL-3 | file LICENSE
NeedsCompilation:	yes
Materials:	README NEWS
CRAN checks:	predkmeans results

Documentation:

Reference manual:

predkmeans.pdf

Downloads:

Package source:	predkmeans_0.1.1.tar.gz
Windows binaries:	r-devel: predkmeans_0.1.1.zip, r-release: predkmeans_0.1.1.zip, r-oldrel: predkmeans_0.1.1.zip
macOS binaries:	r-release (arm64): predkmeans_0.1.1.tgz, r-oldrel (arm64): predkmeans_0.1.1.tgz, r-release (x86_64): predkmeans_0.1.1.tgz, r-oldrel (x86_64): predkmeans_0.1.1.tgz
Old sources:	predkmeans archive

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