Open Access Open Access  Restricted Access Subscription Access

Estimation of Shape Parameter and Measure of Dispersion of Inverse Gaussian Distribution Using Prior Information

Housila P. Singh, Sheetal Pandit


For estimating the shape parameter and measure of dispersion of the Inverse Gaussian distribution, a general class of estimators using prior information has been defined. The resulting estimators have been compared with minimum mean squared error estimator, uniformly minimum variance unbiased estimator, Pandey and Malik (1988) estimator. Realistic conditions have been obtained under which the suggested estimators are better than the well-known minimum mean squared error estimator and uniformly minimum variance unbiased estimator. Numerical illustrations are given in the support of the proposed study.


Inverse Gaussian distribution, Shrinkage estimators, Prior Information

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.