Statistical Analysis of Location Parameter of Inverse Gaussian Distribution Under Noninformative Priors

  • Nida Khan Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
  • Muhammad Aslam Department of Mathematics and Statistics, Riphah International University, Islamabad, Pakistan.
Keywords: Bayesian estimation, noninformative prior, Jeffreys prior, loss function, Bayes estimator, Bayes risk, simulation study


Bayesian estimation for location parameter of the inverse Gaussian distribution is presented in this paper. Noninformative priors (Uniform and Jeffreys) are assumed to be the prior distributions for the location parameter as the shape parameter of the distribution is considered to be known. Four loss functions: Squared error, Trigonometric, Squared logarithmic and Linex are used for estimation. Bayes risks are obtained to find the best Bayes estimator through simulation study and real life data


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How to Cite
Khan, N., & Aslam, M. (2019). Statistical Analysis of Location Parameter of Inverse Gaussian Distribution Under Noninformative Priors. Journal of Quantitative Methods, 3(2), 62-76.