car (version 2.0-14)

testTransform: Likelihood-Ratio Tests for Univariate or Multivariate Power Transformations to Normality

Description

testTransform computes likelihood ratio tests for particular transformations based on powerTransform objects.

Usage

testTransform(object, lambda)

## S3 method for class 'powerTransform':
testTransform(object, lambda=rep(1, dim(object$y)[2]))

Arguments

object
An object created by a call to estimateTransform or powerTransform.
lambda
A vector of values of length equal to the number of variables to be transformed.

Value

  • A data frame with one row giving the value of the test statistic, its degrees of freedom, and a p-value. The test is the likelihood ratio test, comparing the value of the log-likelihood at the hypothesized value to the value of the log-likelihood at the maximum likelihood estimate.

Details

The function powerTransform is used to estimate a power transformation for a univariate or multivariate sample or multiple linear regression problem, using the method of Box and Cox (1964). It is usual to round the estimates to nearby convenient values, and this function is use to compulte a likelihood ratio test for values of the transformation parameter other than the ml estimate. This is a generic function, but with only one method, for objects of class powerTransform.

References

Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations. Journal of the Royal Statisistical Society, Series B. 26 211-46. Cook, R. D. and Weisberg, S. (1999) Applied Regression Including Computing and Graphics. Wiley. Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage. Weisberg, S. (2005) Applied Linear Regression, Third Edition. Wiley.

See Also

powerTransform.

Examples

Run this code
summary(a3 <- powerTransform(cbind(len, ADT, trks, sigs1) ~ hwy, Highway1))
# test lambda = (0 0 0 -1)
testTransform(a3, c(0, 0, 0, -1))

Run the code above in your browser using DataCamp Workspace