A NEW PROCEDURE : BAYESIAN SELECTION TO FIND THE BEST OF GEOMETRIC POPULATION UNDER GENERAL LOSS FUNCTION
DOI:
https://doi.org/10.31642/JoKMC/2018/010606Keywords:
T- open, l- continuousAbstract
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 .
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Copyright (c) 2014 Samira Faisal Hathoot
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