Package: kcmeans 0.1.0.9000

kcmeans: Conditional Expectation Function Estimation with K-Conditional-Means

Implementation of the KCMeans regression estimator studied by Wiemann (2023) <arxiv:2311.17021> for expectation function estimation conditional on categorical variables. Computation leverages the unconditional KMeans implementation in one dimension using dynamic programming algorithm of Wang and Song (2011) <doi:10.32614/RJ-2011-015>, allowing for global solutions in time polynomial in the number of observed categories.

Authors:Thomas Wiemann [aut, cre]

kcmeans_0.1.0.9000.tar.gz
kcmeans_0.1.0.9000.zip(r-4.7-any)kcmeans_0.1.0.9000.zip(r-4.6-any)kcmeans_0.1.0.9000.zip(r-4.5-any)
kcmeans_0.1.0.9000.tgz(r-4.6-any)kcmeans_0.1.0.9000.tgz(r-4.5-any)
kcmeans_0.1.0.9000.tar.gz(r-4.7-any)kcmeans_0.1.0.9000.tar.gz(r-4.6-any)
kcmeans_0.1.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
kcmeans/json (API)

# Install 'kcmeans' in R:

install.packages('kcmeans', repos = c('https://thomaswiemann.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/thomaswiemann/kcmeans/issues

On CRAN:

4.65 score 3 stars 1 packages 5 scripts 247 downloads 1 exports 7 dependencies

Last updated from:ecd07a6b4a. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	123
source / vignettes	OK	183
linux-release-x86_64	OK	116
macos-release-arm64	OK	182
macos-oldrel-arm64	OK	128
windows-devel	OK	79
windows-release	OK	72
windows-oldrel	OK	75
wasm-release	OK	141