NDLI: Estimating a transformation and its effect on Box-CoxT-ratio

Content Provider	Springer Nature Link
Author	Yang, Zhelin
Copyright Year	1999
Abstract	This article concernsi) the stochastic behavior of the Box-Cox transformation estimator andii) the effect of estimating a transformation on the Box-CoxT-ratio used for the post-transformation analysis. It is shown that the transformation estimator depends on three factors: the model structure, the mean-spread and the error standard deviation σ$_{0}$. In general, a structured model is able to estimate the transformation very well; an unstructured model can do well also unless the mean-spread and σ$_{0}$ are both small; and a one-mean mode can give a poor-estimate if σ$_{0}$ is small. When the sample is not large, it is shown that the unconditional effect of estimating a transformation on the Box-CoxT-ratio is generally small, and the “conditional” effect is also negligible in most of the situations except the case of one-way ANOVA with small σ$_{0}$. Extensive Monte Carlo simulations are performed to support the theoretical findings.
Starting Page	167
Ending Page	190
Page Count	24
File Format	PDF
ISSN	11330686
Journal	Test
Volume Number	8
Issue Number	1
e-ISSN	18638260
Language	English
Publisher	Springer-Verlag
Publisher Date	1999-01-01
Publisher Institution	Spanish Society of Statistics and Operations Research
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Asymptotic expansion Box-Cox transformation Tolerance and confidence regions Statistics Statistical Theory and Methods Statistics for Business/Economics/Mathematical Finance/Insurance
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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