seedpls | R Documentation |

Returns partial least squares estimates through iterative projections. And, the function results in subclass "seedpls".

seedpls(X, Y, u=5, scale=FALSE)

`X` |
numeric matrix (n * p), a set of predictors |

`Y` |
numeric vector or matrix (n * r), responses (it can be multi-dimensional) |

`u` |
numeric, the number of projections. The default is 5. |

`scale` |
logical, FALSE is default. If TRUE, each predictor is standardized with mean 0 and variance 1 |

`coef` |
the estimated coefficients for each iterative projection upto u |

`u` |
the maximum number of projections |

`X` |
Predictors |

`Y` |
Response |

`scale` |
status of scaling predictors |

######## data(cookie) ######## data(cookie) myseq<-seq(141,651,by=2) X<-as.matrix(cookie[-c(23,61),myseq]) Y<-as.matrix(cookie[-c(23,61),701:704]) fit.pls1 <- seedpls(X,Y[,1]) ## one-dimensional response fit.pls2 <- seedpls(X,Y, u=6, scale=TRUE) ## four-dimensional response

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.