Likelihood-Ratio Tests for Univariate or Multivariate Power Transformations to Normality
testTransform computes likelihood ratio tests for particular transformations
testTransform(object, lambda) ## S3 method for class 'powerTransform': testTransform(object, lambda=rep(1, dim(object$y)))
- An object created by a call to
- A vector of values of length equal to the number of variables to be transformed.
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
- 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.
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. (2014) Applied Linear Regression, Fourth Edition, Wiley.
summary(a3 <- powerTransform(cbind(len, ADT, trks, sigs1) ~ hwy, Highway1)) # test lambda = (0 0 0 -1) testTransform(a3, c(0, 0, 0, -1))