Efficient Monte Carlo computation of Fisher information matrix using prior information
Computational Statistics & Data Analysis
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An alternative inverse Gaussian distribution expressed in terms of the Bessel function is introduced. Both theoretical and empirical motivation is provided. Various particular cases and expressions for moments are derived. Estimation procedures by the method of moments and the method of maximum likelihood as well as the associated Fisher information matrix are derived. A simulation study is performed to investigate the asymptotic distribution of an associated boundary crossing variable. Finally, an application is illustrated to show that the proposed distribution can be a better model for reliability data than one based on the standard inverse Gaussian distribution.