Probabilistic Model building using the Transformation Entropy for the Burr type –xii Distribution

Abstract

Entropy define as uncertainty measure has been transfared by using the cumulative distribution function and reliability function for the Burr type – xii. In the case of data which suffer from volatility to build a model the probability distribution on every failure of a sample after achieving limitations function, probabilistic distribution. Has been derived formula probability distribution of the new transfer application entropy on the probability distribution of continuous Burr Type-XII and tested a new function and found that it achieved the conditions function probability, been derived mean and function probabilistic aggregate in order to be approved in the generation of data for the purpose of implementation of simulation experiments. Was then estimate parameters of the probability distribution that has been extracted from the distribution formula for the function of every failure using a method as possible the greatest and the way White and the way the estimated mixed, and comparison between the adoption of the standard average squares error (MSE) to compare the results using the method of simulation in the demo to get to the advantage estimators and volumes of different samples to my teacher and measurement form of distribution. The results reveal that the mixed estimated parameter is the best form either parameter shape, and the results showed that the best estimated of scale parameters are the White estimator