Abstract
For the two-parameter inverse Gaussian distribution denoted by IG(μ, λ), the authors employ a linear Bayes procedure to estimate the parameters μ and λ. The superiority of the proposed linear Bayes estimator (LBE) over both the classical UMVUE and the maximum likelihood estimator (MLE) is established in terms of the mean squared error matrix (MSEM) criterion. Compared with the usual Bayes estimator, which is obtained by an MCMC method, the proposed LBE is simple and easy to use. Some numerical results are presented to verify that the LBE performs well.
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