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Unbiased Estimation for a Multivariate Exponential whose Components have a Common Shift

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  • Bordes, Laurent
  • Nikulin, Mikhail
  • Voinov, Vassily
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    Abstract

    It is shown that for independent and identically distributed random vectors, for which the components are independent and exponentially distributed with a common shift, we can construct unbiased estimators of their density, derived from the Uniform Minimum Variance Unbiased Estimator (UMVUE) of their distribution function. As direct applications of the UMVUEs of the density functions we present a Chi-square goodness of fit test of the model, and give two tables of the UMVUEs of some commonly used functions of the unknown parameters of the multivariate exponential model considered in this paper.

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    Bibliographic Info

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

    Volume (Year): 63 (1997)
    Issue (Month): 2 (November)
    Pages: 199-221

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    Handle: RePEc:eee:jmvana:v:63:y:1997:i:2:p:199-221

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    Related research

    Keywords: UMVUE multivariate exponential unbiased estimators of density sufficient statistic chi-square test shift and scale parameters conditional limit theorem;

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    1. Pal N. & Sinha Β. K., 1990. "Estimation Of A Common Location Of Several Exponentials," Statistics & Risk Modeling, De Gruyter, vol. 8(1), pages 27-36, January.
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