A NEW PROCEDURE : BAYESIAN SELECTION TO FIND THE BEST OF GEOMETRIC POPULATION UNDER GENERAL LOSS FUNCTION | ||
| Journal of Kufa for Mathematics and Computer | ||
| Article 1, Volume 1, Issue 6, September 2013, Pages 49-56 | ||
| Author | ||
| Samira Faisal Hathoot | ||
| Abstract | ||
| In many practical situations the experimenter is confronted with the problem of choosing the best one of a number of populations or categories or ranking them according to their performance . This paper derives a procedure for selecting the better of Two Geometric populations employing a decision-theoretic Bayesian framework with Beta prior under general loss function . the numerical results for this procedure are given by using Math Works Matlab ver 7.0.1 with different loss functions constant , linear and quadratic , where in one equation we can obtain the Bayes risk for the three types of the loss functions : constant , linear and quadratic . | ||
| Keywords | ||
| selection procedure; general loss function; beta prior; Bayesian decision theory; Bayes risk | ||
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