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-staging / r-plsdof
conda install conda-forge::r-plsdofconda install conda-forge/label/cf201901::r-plsdofconda install conda-forge/label/cf202003::r-plsdofconda install conda-forge/label/gcc7::r-plsdof