DiffXTables: Pattern Heterogeneity via Distributional Differences Across Contingency Tables

Statistical hypothesis testing of pattern heterogeneity via differences in underlying distributions across two or more contingency tables. Three tests are included: the comparative chi-squared test (Song et al, 2014) <doi:10.1093/nar/gku086> (Zhang et al, 2015) <doi:10.1093/nar/gkv358>, the Sharma-Song test, and the heterogeneity test. Under the null hypothesis that row and column variables are statistically independent and joint distributions are equal, their test statistics all follow an asymptotically chi-squared distribution. These options test for heterogeneous patterns that differ in either the first order (marginal) or the second order (joint distribution deviation from product of marginals). Second-order differences may reveal more fundamental changes than first-order differences across heterogeneous patterns.

Version: 0.0.2
Depends: R (≥ 3.0)
Imports: Matrix
Suggests: Ckmeans.1d.dp, FunChisq, knitr, rmarkdown, testthat
Published: 2019-11-12
Author: Ruby Sharma [aut], Joe Song ORCID iD [aut, cre]
Maintainer: Joe Song <joemsong at cs.nmsu.edu>
License: LGPL (≥ 3)
NeedsCompilation: no
Citation: DiffXTables citation info
Materials: README NEWS
CRAN checks: DiffXTables results

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Reference manual: DiffXTables.pdf
Vignettes: Using the 'DiffXTables' R package to detect heterogeneity
Package source: DiffXTables_0.0.2.tar.gz
Windows binaries: r-devel: DiffXTables_0.0.2.zip, r-devel-gcc8: DiffXTables_0.0.2.zip, r-release: DiffXTables_0.0.2.zip, r-oldrel: DiffXTables_0.0.2.zip
OS X binaries: r-release: DiffXTables_0.0.2.tgz, r-oldrel: DiffXTables_0.0.2.tgz
Old sources: DiffXTables archive

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