Partitioning of the independent and joint contributions of each variable in a multivariate data set, to a linear regression by hierarchical decomposition of goodness-of-fit measures of regressions using all subsets of predictors in the data set. (i.e., model (1), (2), ..., (N), (1,2), ..., (1,N), ..., (1,2,3,...,N)). A Z-score based estimate of the 'importance' of each predictor is provided by using a randomisation test.
Version: | 1.0-6 |
Imports: | gtools, betareg, MASS |
Published: | 2020-03-03 |
Author: | Chris Walsh [aut, cre], Ralph Mac Nally [aut] |
Maintainer: | Chris Walsh <cwalsh at unimelb.edu.au> |
BugReports: | https://github.com/cjbwalsh/hier.part/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
NeedsCompilation: | yes |
Citation: | hier.part citation info |
Materials: | README NEWS |
CRAN checks: | hier.part results |
Reference manual: | hier.part.pdf |
Package source: | hier.part_1.0-6.tar.gz |
Windows binaries: | r-devel: hier.part_1.0-6.zip, r-release: hier.part_1.0-6.zip, r-oldrel: hier.part_1.0-6.zip |
macOS binaries: | r-release (arm64): hier.part_1.0-6.tgz, r-oldrel (arm64): hier.part_1.0-6.tgz, r-release (x86_64): hier.part_1.0-6.tgz, r-oldrel (x86_64): hier.part_1.0-6.tgz |
Old sources: | hier.part archive |
Reverse depends: | tvgarch |
Reverse suggests: | FactorsR |
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