MissMech: Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random

To test whether the missing data mechanism, in a set of incompletely observed data, is one of missing completely at random (MCAR). For detailed description see Jamshidian, M. Jalal, S., and Jansen, C. (2014). "MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR)", Journal of Statistical Software, 56(6), 1-31. <https://www.jstatsoft.org/v56/i06/> <doi:10.18637/jss.v056.i06>.

Version: 1.0.4
Depends: R (≥ 2.10)
Imports: graphics, stats
Published: 2024-03-05
DOI: 10.32614/CRAN.package.MissMech
Author: Mortaza Jamshidian [aut], Siavash Jalal [aut], Camden Jansen [aut], Mao Kobayashi [cre]
Maintainer: Mao Kobayashi <kobamao.jp at gmail.com>
BugReports: https://github.com/indenkun/MissMech/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/indenkun/MissMech
NeedsCompilation: no
Citation: MissMech citation info
Materials: README NEWS
CRAN checks: MissMech results

Documentation:

Reference manual: MissMech.pdf

Downloads:

Package source: MissMech_1.0.4.tar.gz
Windows binaries: r-devel: MissMech_1.0.4.zip, r-release: MissMech_1.0.4.zip, r-oldrel: MissMech_1.0.4.zip
macOS binaries: r-release (arm64): MissMech_1.0.4.tgz, r-oldrel (arm64): MissMech_1.0.4.tgz, r-release (x86_64): MissMech_1.0.4.tgz, r-oldrel (x86_64): MissMech_1.0.4.tgz
Old sources: MissMech archive

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