A New Class of Generalized Probability-Weighted Moment Estimators for the Pareto Distribution

Estimation based on probability-weighted moments is a well-established method and an excellent alternative to the classic of or maximum likelihood method, especially for small sample sizes. In this research, we developed new class estimators parameters Pareto type I distribution. A generalization approach foundation estimators. It has advantage being valid in entire parameter space We established asymptotic normality applied them simulated real datasets order illustrate their finite behavior. The results comparisons with most used estimation methods were also analyzed.