Article,

A Note on Adaptive Box-Cox Transformation Parameter in Linear Regression

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International Journal of Research and Innovation in Applied Science (IJRIAS), 1 (4): 01-09 (July 2016)

Abstract

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. In this paper we use six different data sets to implement adaptive maximum likelihood Box-Cox transformation parameter estimation in regression analysis. In addition, we perform random permutation and Monte-Carlo simulation to investigate the performances of the adaptive method.

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