predict.slim: Prediction using a condensed autopls model

In autopls: Partial Least Squares Regression with Backward Selection of Predictors

Description

Applies a model object of class slim originating from autopls to a vector, matrix or to a stack or brick from package raster.

Usage

  ## S3 method for class 'slim'
predict(object, dat, ...)

Arguments

object	object of class slim
dat	vector, matrix, dataframe or imagery (the latter as stack or brick from package raster.
...	logical. Arguments to be passed to method

Details

Elements, columns or layers must have the same number and order as the input predictors for autopls. In case of large image files the function is based on tile processing.

Value

A new vector matrix or image depending on the type of newdata

Author(s)

Sebastian Schmidtlein

See Also

autopls, 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)

  ## condensed model object
  new.model <- slim (model)
  
  ## new data
  new <- murnau.X + 500 

  ## prediction
  predict (new.model, new)

autopls documentation built on May 2, 2019, 9:39 a.m.