Author(s): Ekta Hooda, Darvinder Kumar and Nitin Tanwar

Abstract: Type-II extreme value distribution has been used fro modeling and analysis of several extreme value events relatled to floods, sea currents, and wind speeds. Probability Weighted Moments (PWMs) and Partial probability weighted moments (PPWMs) are of potential interests for estimating parameters of distributions that may be expressed in inverse form. In the present paper, the method of probability-weighted moments developed by Greenwood et al. (1979) and used for estimation of Type-II Extreme value distribution parameters from complete and censored samples. Expressions for Probability-weighted moments and partial probability weighted moments estimators have been derived. Based on the Monte Carlo simulation method, the derived estimators have been compared with the estimators obtained using method of moments and maximum likelihood method in terms of bias and relative efficiency using monte carlo simulation. PWM method is simpler than the other methods like method of moments and maximum likelihood method for the estimation of Fréchet distribution parameters. PWMs estimates result in explicit expressions and therefore, this method may serve as a better alternative for parameter estimation.

Pages: 113-117 | Views: 269 | Downloads: 22

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