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.

Install the latest version of this package by entering the following in R:

`install.packages("plsdof")`

Author | Nicole Kraemer, Mikio L. Braun |

Date of publication | 2014-09-04 15:41:41 |

Maintainer | Nicole Kraemer <kraemer_r_packages@yahoo.de> |

License | GPL (>= 2) |

Version | 0.2-7 |

**benchmark.pls:** Comparison of model selection criteria for Partial Least...

**benchmark.regression:** Comparison of Partial Least Squares Regression, Principal...

**coef.plsdof:** Regression coefficients

**compute.lower.bound:** Lower bound for the Degrees of Freedom

**dA:** Derivative of normalization function

**dnormalize:** Derivative of normalization function

**dvvtz:** First derivative of the projection operator

**first.local.minimum:** Index of the first local minimum.

**information.criteria:** Information criteria

**kernel.pls.fit:** Kernel Partial Least Squares Fit

**krylov:** Krylov sequence

**linear.pls.fit:** Linear Partial Least Squares Fit

**normalize:** Normalization of vectors

**pcr:** Principal Components Regression

**pcr.cv:** Model selection for Princinpal Components regression based on...

**pls.cv:** Model selection for Partial Least Squares based on...

**pls.dof:** Computation of the Degrees of Freedom

**plsdof-package:** Degrees of Freedom and Statistical Inference for Partial...

**pls.ic:** Model selection for Partial Least Squares based on...

**pls.model:** Partial Least Squares

**ridge.cv:** Ridge Regression.

**tr:** Trace of a matrix

**vcov.plsdof:** Variance-covariance matrix

**vvtz:** Projectin operator

benchmark.pls | Man page |

benchmark.regression | Man page |

coef.plsdof | Man page |

compute.lower.bound | Man page |

dA | Man page |

dnormalize | Man page |

dvvtz | Man page |

first.local.minimum | Man page |

information.criteria | Man page |

kernel.pls.fit | Man page |

krylov | Man page |

linear.pls.fit | Man page |

normalize | Man page |

pcr | Man page |

pcr.cv | Man page |

pls.cv | Man page |

plsdof | Man page |

pls.dof | Man page |

plsdof-package | Man page |

pls.ic | Man page |

pls.model | Man page |

ridge.cv | Man page |

tr | Man page |

vcov.plsdof | Man page |

vvtz | Man page |

inst

inst/CITATION

inst/ChangeLog

NAMESPACE

R

R/pls.cv.R
R/compute.lower.bound.R
R/dA.R
R/pls.ic.R
R/vcov.plsdof.R
R/dnormalize.R
R/coef.plsdof.R
R/tr.r
R/linear.pls.fit.R
R/first.local.minimum.R
R/krylov.r
R/ridge.cv.R
R/benchmark.pls.R
R/kernel.pls.fit.R
R/benchmark.regression.R
R/pls.model.R
R/vvtz.r
R/pls.dof.R
R/normalize.R
R/information.criteria.R
R/dvvtz.r
R/pcr.R
R/pcr.cv.R
MD5

DESCRIPTION

man

man/compute.lower.bound.Rd
man/dnormalize.Rd
man/first.local.minimum.Rd
man/dvvtz.Rd
man/vcov.plsdof.Rd
man/ridge.cv.Rd
man/pcr.Rd
man/information.criteria.Rd
man/krylov.Rd
man/pls.ic.Rd
man/coef.plsdof.Rd
man/pls.cv.Rd
man/plsdof-package.Rd
man/linear.pls.fit.Rd
man/pcr.cv.Rd
man/pls.model.Rd
man/kernel.pls.fit.Rd
man/pls.dof.Rd
man/benchmark.regression.Rd
man/benchmark.pls.Rd
man/dA.Rd
man/normalize.Rd
man/tr.Rd
man/vvtz.Rd
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