greedy.wilks

0th

Percentile

Stepwise forward variable selection for classification

Performs a stepwise forward variable/model selection using the Wilk's Lambda criterion.

Keywords
multivariate
Usage
greedy.wilks(X, ...)
## S3 method for class 'default':
greedy.wilks(X, grouping, niveau = 0.2, ...)
## S3 method for class 'formula':
greedy.wilks(formula, data = NULL, ...)
Arguments
X
matrix or data frame (rows=cases, columns=variables)
grouping
class indicator vector
formula
formula of the form groups ~ x1 + x2 + ...
data
data frame (or matrix) containing the explanatory variables
niveau
level for the approximate F-test decision
...
further arguments to be passed to the default method, e.g. niveau
Details

A stepwise forward variable selection is performed. The initial model is defined by starting with the variable which separates the groups most. The model is then extended by including further variables depending on the Wilk's lambda criterion: Select the one which minimizes the Wilk's lambda of the model including the variable if its p-value still shows statistical significance.

Value

  • A list of two components, a formula of the form response ~ list + of + selected + variables, and a data.frame results containing the following variables:
  • varsthe names of the variables in the final model in the order of selection.
  • Wilks.lambdathe appropriate Wilks' lambda for the selected variables.
  • F.statistics.overallthe approximated F-statistic for the so far selected model.
  • p.value.overallthe appropriate p-value of the F-statistic.
  • F.statistics.diffthe approximated F-statistic of the partial Wilks's lambda (for comparing the model including the new variable with the model not including it).
  • p.value.diffthe appropriate p-value of the F-statistic of the partial Wilk's lambda.

concept

  • Stepwise variable selection in classification
  • Wilk's lambda

References

Mardia, K. V. , Kent, J. T. and Bibby, J. M. (1979), Multivariate analysis, Academic Press (New York; London)

See Also

stepclass, manova

Aliases
  • greedy.wilks
  • greedy.wilks.default
  • greedy.wilks.formula
  • print.greedy.wilks
Examples
data(B3)
gw_obj <- greedy.wilks(PHASEN ~ ., data = B3, niveau = 0.1)
gw_obj
## now you can say stuff like
## lda(gw_obj$formula, data = B3)
Documentation reproduced from package klaR, version 0.6-11, License: GPL-2

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