# spls v2.2-3

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## Sparse Partial Least Squares (SPLS) Regression and Classification

Provides functions for fitting a sparse
partial least squares (SPLS) regression and classification
(Chun and Keles (2010) <doi:10.1111/j.1467-9868.2009.00723.x>).

## Functions in spls

Name | Description | |

cv.spls | Compute and plot cross-validated mean squared prediction error for SPLS regression | |

prostate | Prostate Tumor Gene Expression Dataset | |

plot.spls | Plot the coefficient path of SPLS regression | |

predict.sgpls | Make predictions or extract coefficients from a fitted SGPLS model | |

print.spls | Print function for a SPLS object | |

print.sgpls | Print function for a SGPLS object | |

sgpls | Fit SGPLS classification models | |

yeast | Yeast Cell Cycle Dataset | |

spls-internal | Internal SPLS functions | |

predict.spls | Make predictions or extract coefficients from a fitted SPLS model | |

spls | Fit SPLS regression models | |

lymphoma | Lymphoma Gene Expression Dataset | |

splsda | Fit SPLSDA classification models | |

mice | Mice Dataset | |

predict.splsda | Make predictions or extract coefficients from a fitted SPLSDA model | |

print.splsda | Print function for a SPLSDA object | |

cv.splsda | Compute and plot cross-validated error for SPLSDA classification | |

ci.spls | Calculate bootstrapped confidence intervals of SPLS coefficients | |

coefplot.spls | Plot estimated coefficients of the SPLS object | |

correct.spls | Correct the initial SPLS coefficient estimates based on bootstrapped confidence intervals | |

cv.sgpls | Compute and plot the cross-validated error for SGPLS classification | |

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## Vignettes of spls

Name | ||

spls-example.Rnw | ||

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## Last month downloads

## Details

Date | 2019-05-04 |

License | GPL (>= 2) |

NeedsCompilation | no |

Packaged | 2019-05-04 21:53:24 UTC; Share |

Repository | CRAN |

Date/Publication | 2019-05-04 23:10:03 UTC |

imports | MASS , nnet , parallel , pls |

depends | R (>= 2.14) |

Contributors | Dongjun Chung, Hyonho Chun, Sunduz Keles |

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