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On Bayesian inference for the Inverse Gaussian distribution

Author

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  • Betrò, B.
  • Rotondi, R.

Abstract

Bayesian results for the Inverse Gaussian distribution are derived considering a proper prior which enables, under reparametrization in terms of the distribution mean and of the inverse of the squared variation coefficient, of obtaining Bayes estimates of the parameters as well as of their inverses. The complexity of the estimates is shown to be close to the one of the integral of the standard t-distribution.

Suggested Citation

  • Betrò, B. & Rotondi, R., 1991. "On Bayesian inference for the Inverse Gaussian distribution," Statistics & Probability Letters, Elsevier, vol. 11(3), pages 219-224, March.
    • Handle: RePEc:eee:stapro:v:11:y:1991:i:3:p:219-224
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    Cited by:

    1. Tzong-Ru Tsai & Hua Xin & Ya-Yen Fan & Yuhlong Lio, 2022. "Bias-Corrected Maximum Likelihood Estimation and Bayesian Inference for the Process Performance Index Using Inverse Gaussian Distribution," Stats, MDPI, vol. 5(4), pages 1-18, November.
    2. Yanagimoto, Takemi & Ohnishi, Toshio, 2005. "Extensions of the conjugate prior through the Kullback-Leibler separators," Journal of Multivariate Analysis, Elsevier, vol. 92(1), pages 116-133, January.

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