ESTIMATING THE MEAN OF INVERSE GAUSSIAN DISTRIB WTION WITH KNOWN COEFFICIENT OF VARIATION UNDER ENTROPY LOSS
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Abstract:
An estimation problem of the mean µ of an inverse Gaussian distribution IG(µ, C µ) with known coefficient of variation c is treated as a decision problem with entropy loss function. A class of Bayes estimators is constructed, and shown to include MRSE estimator as its closure. Two important members of this class can easily be computed using continued fractions
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Journal title
volume 8 issue 1
pages -
publication date 1997-03-01
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