Ӧ�ø���ͳ�� 2013, 29(2) 121-135 DOI:      ISSN: 1001-4268 CN: 31-1256

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��ͳ�Ĺ���Pareto�ֲ�(Generalized Pareto
Distribution, ���GPD)�IJ�������һ���ֲܷ���״������Լ��. ��:
�ع���(the Method of Moments, ���MOM), ���ʼ�Ȩ�ع���(the
Probability Weighted Moments, ���PWM), L�ع���(���LM),
������Ȼ����(Maximum Likelihood Estimation, ���MLE)��.
��������GDP��ת����ָ���ֲ�����ʵ��ָ���ֲ��������ƵĽ��,
����������(the Least Squares, ���LS)��,
�õ�����������������GPD�IJ�������; �����˹��������н�����̬�ԵĽ��.
���Ʒ������ֲܷ���״����������. ģ����ʾ:
��������Ĺ�����ijЩ��������������GPD��������������, ��MOM, PWM, LM,
�Լ����ڷ�λ������(the Elemental Percentile Method, ���EPM)��.

�ؼ�����
Estimation of Parameters of the Generalized Pareto\\
Distribution by the Least Squares
Chen Haiqing,Cheng Weihu
College of Mathematics and Computer Science, Guizhou Normal College, College of Applied Science, Beijing University of Technology
Abstract:

Traditional estimations of parameters of
the generalized Pareto distribution (GPD) are generally constrained
by the shape parameter of GPD. Such as: the method-of-moments (MOM),
the probability-weighted moments (PWM), L-moments (LM), the maximum
likelihood estimation (MLE) and so on. In this paper we use the fact
that GPD can be transformed into the exponential distribution and
use the results of parameters estimation for the exponential
distribution, than we propose parameters estimators of the
two-parameter or three-parameter GPD by the least squares method.
Some asymptotic results are provided and the proposed method not
constrained by the shape parameter of GPD. A simulation study is
carried out to evaluate the performance of the proposed method and
to compare them with other methods suggested in this paper. The
simulation results indicate that the proposed method performs better
than others in some common situation.

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