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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 219.1 kB | noarch/r-plsdof-0.3_0-r42hc72bb7e_1.tar.bz2  3 years and 2 months ago 1924 main
conda 219.0 kB | noarch/r-plsdof-0.3_0-r41hc72bb7e_1.tar.bz2  3 years and 2 months ago 1956 main
conda 217.8 kB | noarch/r-plsdof-0.3_0-r41hc72bb7e_0.tar.bz2  4 years and 7 months ago 2596 main
conda 218.6 kB | noarch/r-plsdof-0.3_0-r36hc72bb7e_0.tar.bz2  4 years and 9 months ago 2753 main
conda 218.1 kB | noarch/r-plsdof-0.3_0-r40hc72bb7e_0.tar.bz2  4 years and 9 months ago 2691 main

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