Estimation of coefficient of variation in a weighted inverse Gaussian model

Ramesh C. Gupta and Olcay Akman

Applied Stochastic Models and Data Analysis, 1996, vol. 12, issue 4, 255-263

Abstract: The coefficient of variation is an important parameter in many physical, biological and medical sciences. In this paper we study the estimation of the square of the coefficient of variation in a weighted inverse Gaussian model which is a mixture of the inverse Gaussian and the length biased inverse Gaussian distribution. This represents a rich family of distributions for different values of the mixing parameter and can be used for modelling various life testing situations. The maximum likelihood as well as the Bayes estimates of the parameters are obtained. These estimates are used to derive the estimates of the square of the coefficient of variation of the model under study. Several important data sets are analysed to illustrate the results. © 1996 John Wiley & Sons, Ltd.

Date: 1996
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https://doi.org/10.1002/(SICI)1099-0747(199612)12:43.0.CO;2-R

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmda:v:12:y:1996:i:4:p:255-263

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