Estimating the parameter of Burr-type X model based on fuzzy numbers

Burr type X distribution has increasing importance in several areas of applications such as lifetime tests, health, agriculture, biology, and other sciences. In classical approaches ,estimation of Burr-type X parameter is dealing with precise information. But, in practice, real observations of continuous quantities are not precise numbers. The best description of such data is by so-called fuzzy numbers. Inthis paper, we consider the the of estimating the parameter of Burr-type X distribution when the available observations are described in terms of fuzzy numbers. The maximum likelihood estimate of the unknown parameter and observed Fisher information are obtained. Monte Carlo simulations are performed in order to assess the accuracy of the proprop methods.

Keywords:

Fuzzy data analysis , Burr-type X distribution , Maximum likelihood estimation , Monte Carlo simulation.