ESTIMATING FUZZY HAZARD RATE OF THREE PARAMETERS WEIBULL DISTRIBUTION
It is noticed there are many researches and studies in the field of statistics particularly in the field of hazard aiming in order to obtain estimators of very high standard of competency or tainted by instances of uncertainty, which often leads the researcher to estimate the fuzzy hazard functions instead of the usual hazard function, it is the most comprehensive and representative of the data for which the hazard function is to be applied. This paper deals with estimating of fuzzy hazard rate function of three parameters Weibull, methods of Moments Estimators (MOE), maximum likelihood estimators (MLE), and Regression method. The comparison is done by simulation method using different sample size (n=40,60, 80) and initial values of (b,c,δ)(b: scale, c: shape , δ: location parameter). after the parameters are estimated by different three methods (MLE, MOM, PEC(Regression) ; the values of ( t_i ) is generated from C.D.F, using inverse transformation. set of five values of ( t_i ) have been taken for application and estimation process. The goal of this process is to get the lowest value of the Mean square error, many fidelity criteria have been computed and the results have been discussed.
Keywords: Fuzzy hazard rate, Weibull Distribution, Maximum Likelihood Estimator (MLE), Moments estimator (MOM), Percentiles