Nonlinear weighted least squares estimation of a three-parameter Weibull density with a nonparametric start

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摘要

This paper is concerned with the parameter estimation problem for the three-parameter Weibull density which is widely employed as a model in reliability and lifetime studies. Our approach is a combination of nonparametric and parametric methods. The basic idea is to start with an initial nonparametric density estimate which needs to be as good as possible, and then apply the nonlinear least squares method to estimate the unknown parameters. As a main result, a theorem on the existence of the least squares estimate is obtained. Some simulations are given to show that our approach is satisfactory if the initial density is of good enough quality.

论文关键词:65D10,62J02,62G07,62N05,Three-parameter Weibull density,Data fitting,Nonlinear least squares,Least squares estimate,Existence problem

论文评审过程:Received 6 June 2008, Available online 1 October 2008.

论文官网地址:https://doi.org/10.1016/j.cam.2008.09.025