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conda-forge / packages / r-grpreg

Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge.

copied from cf-staging / r-grpreg

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Type Size Name Uploaded Downloads Labels
conda 372.8 kB | win-64/r-grpreg-3.2_1-r36hda5aaf8_1.tar.bz2  5 years and 5 months ago 1375 main cf202003
conda 370.9 kB | win-64/r-grpreg-3.2_1-r35hda5aaf8_1.tar.bz2  5 years and 5 months ago 1376 main cf202003
conda 359.0 kB | osx-64/r-grpreg-3.2_1-r35h159158b_1.tar.bz2  5 years and 5 months ago 363 main cf202003
conda 360.9 kB | osx-64/r-grpreg-3.2_1-r36h159158b_1.tar.bz2  5 years and 5 months ago 355 main cf202003
conda 357.9 kB | linux-64/r-grpreg-3.2_1-r35hcdcec82_1.tar.bz2  5 years and 5 months ago 3685 main cf202003
conda 359.7 kB | linux-64/r-grpreg-3.2_1-r36hcdcec82_1.tar.bz2  5 years and 5 months ago 3674 main cf202003
conda 359.4 kB | osx-64/r-grpreg-3.2_1-r351h46e59ec_0.tar.bz2  5 years and 9 months ago 370 main cf202003
conda 357.8 kB | linux-64/r-grpreg-3.2_1-r351h96ca727_0.tar.bz2  5 years and 9 months ago 4096 main cf202003
conda 370.4 kB | win-64/r-grpreg-3.2_1-r351h6115d3f_0.tar.bz2  5 years and 9 months ago 1483 main cf202003
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