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practicalSigni

Practical Significance Ranking of Regressors and Exact t Density

Installation

About

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.

Key Metrics

Version 0.1.2
R ≥ 4.3.0
Published 2023-12-01 156 days ago
Needs compilation? no
License GPL-2
License GPL-3
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Maintainer

Maintainer

Hrishikesh Vinod

vinod@fordham.edu

Authors

Hrishikesh Vinod

aut / cre

Material

NEWS
Reference manual
Package source

Vignettes

practicalSigni-vignette
practicalSigni-vignette2

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

practicalSigni archive

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