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Decomposability of high-dimensional diversity measures: Quasi-U-statistics, martingales and nonstandard asymptotics

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Author Info
Pinheiro, Aluísio
Sen, Pranab Kumar
Pinheiro, Hildete Prisco
Abstract

In analyses of complex diversity, especially that arising in genetics, genomics, ecology and other high-dimensional (and sometimes low-sample-size) data models, typically subgroup decomposability (analogous to ANOVA decomposability) arises. For group divergence of diversity measures in a high-dimension low-sample-size scenario, it is shown that Hamming distance type statistics lead to a general class of quasi-U-statistics having, under the hypothesis of homogeneity, a martingale (array) property, providing a key to the study of general (nonstandard) asymptotics. Neither the stochastic independence nor homogeneity of the marginal probability laws plays a basic role. A genomic MANOVA model is presented as an illustration.

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Article provided by Elsevier in its journal Journal of Multivariate Analysis.

Volume (Year): 100 (2009)
Issue (Month): 8 (September)
Pages: 1645-1656
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Handle: RePEc:eee:jmvana:v:100:y:2009:i:8:p:1645-1656

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Related research
Keywords: Categorical Data Dependence DNA Genomics Hamming distance Orthogonal system Permutation measure Second-order asymptotics Second-order decomposability;

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