Estimation of parameters of the shifted Gompertz distribution using least squares, maximum likelihood and moments methods

作者:

Highlights:

摘要

Nonlinear least squares procedures for estimating the parameters of the shifted Gompertz distribution are proposed. Simulation studies are carried out to compare weighted and unweighted least squares methods, the maximum likelihood method and method of moments. This work concludes that least squares methods via weighting factors to estimate the parameters of this probability distribution give a better performance than unweighted least squares methods, showing the importance of weighting factors. Besides, results of this simulation study show that a good performance is obtained using the maximum likelihood method and the estimators obtained with more bias are those of the method of moments.

论文关键词:Shifted Gompertz distribution,Least squares estimation,Maximum likelihood estimation,Moment estimation,Quantile function,Simulation

论文评审过程:Received 16 January 2012, Revised 6 May 2013, Available online 18 July 2013.

论文官网地址:https://doi.org/10.1016/j.cam.2013.07.004