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Biases of the maximum likelihood and Cohen-Sackrowitz estimators for the tree-order model

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  • Chaudhuri, Sanjay
  • Perlman, Michael D.
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    Abstract

    Consider s+1 univariate normal populations with common variance [sigma]2 and means [mu]i, i=0,1,...,s, constrained by the tree-order restrictions [mu]i[greater-or-equal, slanted][mu]0, i=1,2,...,s. For certain sequences [mu]0,[mu]1,... the maximum likelihood-based estimator (MLBE) of [mu]0 diverges to -[infinity] as s-->[infinity] and its bias is unbounded. By contrast, the bias of an alternative estimator of [mu]0 proposed by Cohen and Sackrowitz (J. Statist. Plan. Infer. 107 (2002) 89-101) remains bounded. In this note the biases of the MLBEs of the other components [mu]1,[mu]2,... are studied and compared to the biases of the corresponding Cohen-Sackrowitz estimators (CSE). Unlike the MLBE of [mu]0, the MLBEs of [mu]i for i[greater-or-equal, slanted]1, are asymptotically unbiased in most cases. By contrast, the CSEs of [mu]i, i=1,2,...,s more often have nonzero asymptotic bias.

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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 71 (2005)
    Issue (Month): 3 (March)
    Pages: 267-276

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    Handle: RePEc:eee:stapro:v:71:y:2005:i:3:p:267-276

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    Related research

    Keywords: Order-restricted inference Tree order Maximum likelihood estimator Cohen-Sackrowitz estimator Bias;

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