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The superiority of bayes linear unbiased minimum variance estimator under balanced loss

Miao Bai-qi

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Abstract

The superiority of Bayes linear unbiased minimum variance(BLUMV) estimator with respect to least square(LS) estimator of unknown parameter was studied in terms of the balanced loss risk function criterion.The superiority of the BLUMV estimator over LS estimator was studied in terms of the predictive Pitman closeness(PRPC) criterion.

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What this paper is about

The superiority of Bayes linear unbiased minimum variance(BLUMV) estimator with respect to least square(LS) estimator of unknown parameter was studied in terms of the balanced loss risk function criterion.The superiority of the BLUMV estimator over LS estimator was studied in terms of the predictive Pitman closeness(PRPC) criterion.

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Available abstract

The superiority of Bayes linear unbiased minimum variance(BLUMV) estimator with respect to least square(LS) estimator of unknown parameter was studied in terms of the balanced loss risk function criterion.The superiority of the BLUMV estimator over LS estimator was studied in terms of the predictive Pitman closeness(PRPC) criterion.

Key concepts: Minimum-variance unbiased estimator, Bias of an estimator, Mathematics, Efficient estimator, Stein's unbiased risk estimate, Statistics, Mean squared error, Estimator

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