extract.autopls {autopls}R Documentation

Extract information from a fitted autopls model

Description

Functions to extract information from autopls objects: crossvalidation, fitted values, regression coefficients, residuals, scores, loadings, latent vectors used, underlying run.

Usage

  predicted (object)
  get.lv (object)
  get.iter (object)
  slim (object)
  ## S3 method for class 'autopls'
scores(object, ...)
  ## S3 method for class 'autopls'
loadings(object, ...)
  ## S3 method for class 'autopls'
fitted(object, ...)
  ## S3 method for class 'autopls'
coef(object, intercept = FALSE, ...)
  ## S3 method for class 'slim'
coef(object, intercept = FALSE, ...)
  ## S3 method for class 'autopls'
residuals(object, ...)

Arguments

object

object of class autopls

intercept

logical. Should intercept be given?

...

logical. Arguments to be passed to methods

Details

Provides convenience wrappers for extract functions in package pls. More details are given here: coef.mvr. Other functions extract information specific for autopls objects: get.lv, get.iter or condense the model information to a memory saving object of class slim that can be used for predictions with predict.slim. This makes sense if large pedictor data sets result in huge autopls model objects that are difficult to handle.

Value

see coef.mvr. get.iter returns the run in the autopls backwards selection procedure that has been used for the current model. get.lv returns the number of latent vectors used for the present model. predicted returns the predictions in model validation while fitted returns the predictions in model calibration. slim returns an object of class slim.

Note

If you want to make full use of the extract functions in the pls package assign class mvr to the model object.

Reducing a model to an object of class slim means loosing plotting options.

Author(s)

Sebastian Schmidtlein, links to code from package pls by Ron Wehrens and Bjørn-Helge Mevik.

See Also

autopls, metaval, set.iter, set.lv, predict.slim

Examples

  ## load predictor and response data to the current environment
  data (murnau.X)
  data (murnau.Y)
  
  ## call autopls with the standard options
  model <- autopls (murnau.Y ~ murnau.X)
  
  ## get fitted values
  fitted(model)

[Package autopls version 1.3 Index]