TY - JOUR ID - TI - A NEW PROCEDURE : BAYESIAN SELECTION TO FIND THE BEST OF GEOMETRIC POPULATION UNDER GENERAL LOSS FUNCTION AU - Samira Faisal Hathoot سميرة فيصل حطحوط PY - 2012 VL - 1 IS - 6 SP - 49 EP - 56 JO - Journal of Kufa for Mathematics and Computer مجلة الكوفة للرياضيات والحاسوب SN - 11712076 AB - In many practical situations theexperimenter is confronted with the problem ofchoosing the best one of a number ofpopulations or categories or ranking themaccording to their performance . This paperderives a procedure for selecting the better ofTwo Geometric populations employing adecision-theoretic Bayesian framework withBeta prior under general loss function .the numerical results for this procedureare given by using Math Works Matlab ver 7.0.1with different loss functions constant , linear andquadratic , where in one equation we can obtainthe Bayes risk for the three types of the lossfunctions : constant , linear and quadratic .

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