fastmit: Fast Mutual Information Based Independence Test

A mutual information estimator based on k-nearest neighbor method proposed by A. Kraskov, et al. (2004) <doi:10.1103/PhysRevE.69.066138> to measure general dependence and the time complexity for our estimator is only squared to the sample size, which is faster than other statistics. Besides, an implementation of mutual information based independence test is provided for analyzing multivariate data in Euclidean space (T B. Berrett, et al. (2019) <doi:10.1093/biomet/asz024>); furthermore, we extend it to tackle datasets in metric spaces.

Version: 0.1.1
Imports: Rcpp, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat
Published: 2019-12-30
Author: Shiyun Lin [aut, cre], Jin Zhu [aut], Wenliang Pan [aut], Xueqin Wang [aut], SC2S2 [cph]
Maintainer: Shiyun Lin <linshy27 at mail2.sysu.edu.cn>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: fastmit results

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Reference manual: fastmit.pdf
Package source: fastmit_0.1.1.tar.gz
Windows binaries: r-prerelease: fastmit_0.1.1.zip, r-release: fastmit_0.1.1.zip, r-oldrel: fastmit_0.1.1.zip
macOS binaries: r-prerelease: fastmit_0.1.1.tgz, r-release: fastmit_0.1.1.tgz, r-oldrel: fastmit_0.1.1.tgz

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