A consistent method of estimation for the parameters of the three-parameter inverse Gaussian distribution

Abstract

In this paper, we propose a consistent method of estimation for the parameters of the three-parameter inverse Gaussian distribution. We then discuss some properties of these estimators and show by means of a Monte Carlo simulation study that the proposed estimators perform better than some other prominent estimators in terms of bias and root mean squared error. Finally, we present two real-life examples to illustrate the method of inference developed here.

Keywords:

• maximum likelihood method
• mixed moments method
• conditional method of moments
• order statistics
• threshold parameter
• consistency

AMS Subject Classification :

• 62F10
• 62F86

Acknowledgements

The authors are grateful to the referee for useful comments and suggestions which led to improvements of the manuscript. Hideki Nagatsuka was partially supported by the Grant-in-Aid for Young Scientists (B) 21710155, The Ministry of Education, Culture, Sports, Science and Technology, Japan.