Package: WLogit 2.1
WLogit: Variable Selection in High-Dimensional Logistic Regression Models using a Whitening Approach
It proposes a novel variable selection approach in classification problem that takes into account the correlations that may exist between the predictors of the design matrix in a high-dimensional logistic model. Our approach consists in rewriting the initial high-dimensional logistic model to remove the correlation between the predictors and in applying the generalized Lasso criterion.
Authors:
WLogit_2.1.tar.gz
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WLogit.pdf |WLogit.html✨
WLogit/json (API)
# Install 'WLogit' in R: |
install.packages('WLogit', repos = c('https://clavie3009.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:921ec1a7a4. Checks:1 OK, 8 WARNING. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 08 2025 |
R-4.5-win | WARNING | Mar 08 2025 |
R-4.5-mac | WARNING | Mar 08 2025 |
R-4.5-linux | WARNING | Mar 08 2025 |
R-4.4-win | WARNING | Mar 08 2025 |
R-4.4-mac | WARNING | Mar 08 2025 |
R-4.4-linux | WARNING | Mar 08 2025 |
R-4.3-win | WARNING | Mar 08 2025 |
R-4.3-mac | WARNING | Mar 08 2025 |
Exports:CalculPxCalculWeightRefit_glmThresholdingtoptop_threshWhiteningLogitWorkingResp
Dependencies:abindassertthatbackportsbootbroomcarcarDataclicodetoolscolorspacecoopcorpcorcorrplotcowplotcpp11cvCovEstdata.tableDerivdigestdoBydplyrfansifarverforeachFormulafuturefuture.applygenericsgenlassoggplot2ggpubrggrepelggsciggsignifglmnetglobalsgluegridExtragtableigraphisobanditeratorslabelinglatticelifecyclelistenvlme4magrittrMASSMatrixMatrixModelsmatrixStatsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivorigamiparallellypbkrtestpillarpkgconfigpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangRMTstatRSpectrarstatixscalesshapeSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr