Package: practicalSigni
Type: Package
Title: Practical Significance Ranking of Regressors and Exact t Density
Version: 0.1.2
Date: 2023-11-29
Authors@R: c(person("Hrishikesh", "Vinod", role = c("aut", "cre"),
      email= "vinod@fordham.edu"))
Encoding: UTF-8
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
VignetteBuilder: R.rsp
Description: 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.
   Taraldsen's exact density for sampling distribution of correlations added.
License: GPL (>= 2)
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-11-30 20:51:41 UTC; vinod
Author: Hrishikesh Vinod [aut, cre]
Maintainer: Hrishikesh Vinod <vinod@fordham.edu>
Repository: CRAN
Date/Publication: 2023-12-01 09:50:02 UTC
Built: R 4.6.0; ; 2026-04-25 14:14:24 UTC; unix
