PARAMETER ESTIMATION FOR PARETO DISTRIBUTION AND TYP E-I I FUZZY LOGIC

While parameter estimation by the classical methods there are anumber of assumptions need to be satisfied, in the linear regression analysis. One of them is errors are normally distributed. In this work, the case that independent variable has Pareto distribution to be discussed and an algorithm using adaptive networks suggested to parameter estimation where the k which is one of the parameters of the fuzzy membership functions is fuzzy. Also the parameter of fuzzy membership function is fuzzy the estimation process is based on type-II fuzzy logic.

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