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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 218.9 kB | noarch/r-plsdof-0.4_0-r44hc72bb7e_1.conda  3 months and 20 days ago 236 main
conda 219.1 kB | noarch/r-plsdof-0.4_0-r45hc72bb7e_1.conda  3 months and 20 days ago 255 main
conda 215.8 kB | noarch/r-plsdof-0.4_0-r43hc72bb7e_0.conda  3 months and 24 days ago 247 main
conda 219.1 kB | noarch/r-plsdof-0.4_0-r44hc72bb7e_0.conda  3 months and 24 days ago 234 main

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