practicalSigni: Practical Significance Ranking of Regressors

Consider a possibly nonlinear nonparametric regression with p regressors. We provide evaluations by 13 methods to rank regressors by their practical significance or importance using various methods, including machine learning tools. Comprehensive methods are as follows. m6=Generalized partial correlation coefficient or GPCC by Vinod (2021)<doi:10.1007/s10614-021-10190-x> and Vinod (2022)<https://www.mdpi.com/1911-8074/15/1/32>. m7= a generalization of psychologists' effect size incorporating nonlinearity and many variables. m8= local linear partial (dy/dxi) using the 'np' package for kernel regressions. m9= partial (dy/dxi) using the 'NNS' package. m10= importance measure using the 'NNS' boost function. m11= Shapley Value measure of importance (cooperative game theory). m12 and m13= two versions of the random forest algorithm.

Version:	0.1.1
Depends:	R (≥ 4.2.0), np (≥ 0.60), xtable (≥ 1.8), generalCorr (≥ 1.2), NNS (≥ 0.9), randomForest (≥ 4.7)
Suggests:	R.rsp
Published:	2023-03-29
Author:	Hrishikesh Vinod [aut, cre]
Maintainer:	Hrishikesh Vinod <vinod at fordham.edu>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	practicalSigni results

Documentation:

Reference manual:	practicalSigni.pdf
Vignettes:	practicalSigni-vignette

Downloads:

Package source:	practicalSigni_0.1.1.tar.gz
Windows binaries:	r-devel: practicalSigni_0.1.1.zip, r-release: practicalSigni_0.1.1.zip, r-oldrel: practicalSigni_0.1.1.zip
macOS binaries:	r-release (arm64): practicalSigni_0.1.1.tgz, r-oldrel (arm64): practicalSigni_0.1.1.tgz, r-release (x86_64): practicalSigni_0.1.1.tgz, r-oldrel (x86_64): practicalSigni_0.1.1.tgz
Old sources:	practicalSigni archive

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