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The plsdof package provides Degrees of Freedom estimates for Partial Least Squares (PLS) Regression. Model selection for PLS is based on various information criteria (aic, bic, gmdl) or on cross-validation. Estimates for the mean and covariance of the PLS regression coefficients are available. They allow the construction of approximate confidence intervals and the application of test procedures. Further, cross-validation procedures for Ridge Regression and Principal Components Regression are available.

copied from cf-post-staging / r-plsdof
Type Size Name Uploaded Downloads Labels
conda 158.0 kB | noarch/r-plsdof-0.2_9-r36h6115d3f_2.tar.bz2  6 years and 22 days ago 3583 main
conda 156.9 kB | noarch/r-plsdof-0.2_9-r40h6115d3f_2.tar.bz2  6 years and 22 days ago 3651 main
conda 156.4 kB | noarch/r-plsdof-0.2_9-r35h6115d3f_1.tar.bz2  6 years and 10 months ago 4457 main cf202003
conda 157.9 kB | noarch/r-plsdof-0.2_9-r36h6115d3f_1.tar.bz2  6 years and 10 months ago 4439 main cf202003
conda 156.1 kB | noarch/r-plsdof-0.2_9-r351h6115d3f_0.tar.bz2  7 years and 2 months ago 4815 main cf202003

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