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The Wilson--Hilferty transformation is locally saddlepoint

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  • George R. Terrell

Abstract

Interest in transform methods for normalising test statistics declined with the advent of computers. More recently, small-sample asymptotic methods have been developed to approximate the distributions of complicated test statistics. We propose a generalisation of a classical symmetrising transform to a similar range of statistics. It is shown to behave comparably in a parametric neighbourhood to methods that exploit exponential tilting. Copyright Biometrika Trust 2003, Oxford University Press.

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  • George R. Terrell, 2003. "The Wilson--Hilferty transformation is locally saddlepoint," Biometrika, Biometrika Trust, vol. 90(2), pages 445-453, June.
    • Handle: RePEc:oup:biomet:v:90:y:2003:i:2:p:445-453
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    Cited by:

    1. Gagnon, Philippe & Wang, Yuxi, 2024. "Robust heavy-tailed versions of generalized linear models with applications in actuarial science," Computational Statistics & Data Analysis, Elsevier, vol. 194(C).
    2. Brent D. Burch, 2017. "Distribution-dependent and distribution-free confidence intervals for the variance," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(4), pages 629-648, November.

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