A methodology to implement Box-Cox transformation when no covariate is available

Dag, Osman and Asar, Özgür and Ilk, Ozlem (2014) A methodology to implement Box-Cox transformation when no covariate is available. Communications in Statistics – Simulation and Computation, 43 (7). pp. 1740-1759. ISSN 0361-0918

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Abstract

Box-Cox transformation is one of the most commonly used methodologies when data do not follow normal distribution. However, its use is restricted since it usually requires the availability of covariates. In this paper, the use of a non-informative auxiliary variable is proposed for the implementation of Box-Cox transformation. Simulation studies are conducted to illustrate that the proposed approach is successful in attaining normality under different sample sizes and most of the distributions and in estimating transformation parameter for different sample sizes and mean-variance combinations. Methodology is illustrated on two real life data sets.

Item Type:
Journal Article
Journal or Publication Title:
Communications in Statistics – Simulation and Computation
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2611
Subjects:
?? normalitydata transformation regression analysisnon-informative covariatestatistical distributionsmaximum likelihood estimationmodelling and simulationstatistics and probability ??
ID Code:
63381
Deposited By:
Deposited On:
15 Apr 2013 07:46
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 13:44