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On Non-Normal Invariance Principles for Multi-Response Permutation Procedures
Authors:Peter J. Brockwell  Paul W. Mielke Jr.   John Robinson
Affiliation:Department of Statistics, Colorado State University, Fort Collins;Department of Mathematical Statistics, University of Sydney
Abstract:A non-normal invariance principle is established for a restricted class of univariate multi-response permutation procedures whose distance measure is the square of Euclidean distance. For observations from a distribution with finite second moment, the test statistic is found asymptotically to have a centered chi-squared distribution. Spectral expansions are used to determine the asymptotic distribution for more general distance measures d, and it is shown that if d(x, y) = |x — y|u, u? 2, the asymptotic distribution is not invariant (i.e. it is dependent on the distribution of the observations).
Keywords:Asymptotic distributions    Conditional tests    Distance measures    Invariance principles    Non-invariance    Non-normality    Permutation tests    U-statistics    Weak convergence    Orthogonal expansions
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