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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 218.4 kB | noarch/r-plsdof-0.3_2-r44hc72bb7e_2.conda  1 year and 10 months ago 1393 main
conda 214.4 kB | noarch/r-plsdof-0.3_2-r43hc72bb7e_2.conda  1 year and 10 months ago 1365 main
conda 214.5 kB | noarch/r-plsdof-0.3_2-r43hc72bb7e_1.conda  2 years and 11 months ago 1836 main
conda 214.3 kB | noarch/r-plsdof-0.3_2-r42hc72bb7e_1.conda  2 years and 11 months ago 1793 main
conda 213.3 kB | noarch/r-plsdof-0.3_2-r42hc72bb7e_0.conda  3 years and 5 months ago 2267 main
conda 212.9 kB | noarch/r-plsdof-0.3_2-r41hc72bb7e_0.conda  3 years and 5 months ago 2230 main

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