Parameter estimation for three-parameter generalized Pareto distribution by weighted non linear least squares

Haiqing Chen, Weihu Cheng, Leilei Zhu and Yaohua Rong

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 23, 11440-11449

Abstract: Generalized Pareto distribution (GPD) is widely used to model exceedances over thresholds. In this paper, we propose a new method, called weighted non linear least squares (WNLS), to estimate the parameters of the three-parameter GPD. Some asymptotic results of the proposed method are provided. An extensive simulation is carried out to evaluate the finite sample behaviour of the proposed method and to compare the behaviour with other methods suggested in the literature. The simulation results show that WNLS outperforms other methods in general situations. Finally, the WNLS is applied to analysis the real-life data.

Date: 2017
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DOI: 10.1080/03610926.2016.1202286

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