The use of asymmetric power transformation in data-based quasi-likelihood analysis

  • Wixley R
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Abstract

The object of "data-based" quasi-likelihood analysis is to estimate the variance function from the data itself. Asymmetric power transformations, which are (possibly different) transformations applied to the mean sm; as well as to the observed variable y, are shown to be powerful diagnostic aids for checking first- and second-order model assumptions in the class of quasi-likelihood models. Asymmetric transformations to normality, coupled with the relation between transformation to normality and the variance function in the exponential family is a useful first step in an analysis leading to the optimum data-based variance function. © 1988.

Author-supplied keywords

  • Data-based analysis.
  • Power transformation
  • Quasi-likelihood

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Authors

  • R. A.J. Wixley

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