practicalSigni: Practical Significance Ranking of Regressors and Exact t Density

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)<>. 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. Taraldsen's exact density for sampling distribution of correlations added.

Version: 0.1.2
Depends: R (≥ 4.3.0), np (≥ 0.60), generalCorr (≥ 1.2)
Imports: xtable (≥ 1.8.4), ShapleyValue (≥ 0.2.0), NNS (≥ 0.9), randomForest (≥ 4.7), hypergeo (≥ 1.2.13)
Suggests: R.rsp
Published: 2023-12-01
DOI: 10.32614/CRAN.package.practicalSigni
Author: Hrishikesh Vinod [aut, cre]
Maintainer: Hrishikesh Vinod <vinod at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: practicalSigni results


Reference manual: practicalSigni.pdf
Vignettes: practicalSigni-vignette


Package source: practicalSigni_0.1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): practicalSigni_0.1.2.tgz, r-oldrel (arm64): practicalSigni_0.1.2.tgz, r-release (x86_64): practicalSigni_0.1.2.tgz, r-oldrel (x86_64): practicalSigni_0.1.2.tgz
Old sources: practicalSigni archive


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