DOI QR코드

DOI QR Code

Noninformative Priors for the Coefficient of Variation in Two Inverse Gaussian Distributions

  • Kang, Sang-Gil (Department of Computer and Data Information, Sangji University) ;
  • Kim, Dal-Ho (Department of Statistics, Kyungpook National University) ;
  • Lee, Woo-Dong (Department of Asset Management, Daegu Hanny University)
  • Published : 2008.05.30

Abstract

In this paper, we develop the noninformative priors when the parameter of interest is the common coefficient of variation in two inverse Gaussian distributions. We want to develop the first and second order probability matching priors. But we prove that the second order probability matching prior does not exist. It turns out that the one-at-a-time and two group reference priors satisfy the first order matching criterion but Jeffreys' prior does not. The Bayesian credible intervals based on the one-at-a-time reference prior meet the frequentist target coverage probabilities much better than that of Jeffreys' prior. Some simulations are given.

Keywords

References

  1. Berger, J. O. and Bernardo, J. M. (1989). Estimating a product of means: Bayesian analysis with reference priors, Journal of the American Statistical Association, 84, 200-207 https://doi.org/10.2307/2289864
  2. Berger, J. O. and Bernardo, J. M. (1992). On the development of reference priors (with discussion), In Bayesian Statistics IV, 35-60, eds. J. M. Bernardo, et al., Oxford University Press, Oxford
  3. Bernardo, J. M. (1979). Reference posterior distributions for Bayesian inference, Journal of the Royal Statistical Society, Series B, 41, 113-147
  4. Chhikara, R. S. and Folks, J. L. (1989). The Inverse Gaussian Distribution; Theory, Methodology and Applications, Marcel Dekker, New York
  5. Choi, B. and Kim, K. (2004). Certain multi sample tests for inverse Gaussian populations, Communications in Statistics: Theory & Methods, 33, 1557-1576 https://doi.org/10.1081/STA-120037260
  6. Cox, D. R. and Reid, N. (1987). Parameters orthogonality and approximate conditional inference, Journal of the Royal Statistical Society, Serise B, 49, 1-39
  7. Datta, G. S. and Ghosh, J. K. (1995a). On priors providing frequentist validity for Bayesian inference, Biometrika, 82, 37-45 https://doi.org/10.1093/biomet/82.1.37
  8. Datta, G. S. and Ghosh, M. (1995b). Some remarks on noninformative priors, Journal of the American Statistical Association, 90, 1357-1363 https://doi.org/10.2307/2291526
  9. Datta, G. S. and Ghosh, M. (1996). On the invariance of noninformative priors. The Annals of Statistics, 24, 141-159 https://doi.org/10.1214/aos/1033066203
  10. DiCiccio, T. J. and Steven, E. S. (1994). Frequentist and Bayesian Bartlett correction of test statistics based on adjusted profile likelihood, Journal of the Royal Statistical Society, Series B, 56, 397-408
  11. Folks, J. L. and Chhikara, R. S. (1978). The inverse Gaussian distribution and its statistical application-A review, Journal of the Royal Statistical Society, Series B, 40, 263-289
  12. Ghosh, J. K. and Mukerjee, R. (1992). Non-informative priors (with discussion), In Bayesian Statistics IV, 195-210, eds. J. M. Bernardo, et. al., Oxford University Press, Oxford
  13. Gleser, L. J. and Hwang, J. T. (1987). The non existence of 100(1-$\alpha$)% confidence sets of finite expected diameter in error-in-variables and related models. The Annals of Statistics, 15, 1351-1362 https://doi.org/10.1214/aos/1176350597
  14. Hsieh, H. K. (1990). Inferences on the coe$\pm$cient of variation of an inverse Gaussian distribution, Communications in Statistics-Theory and Methods, 19, 1589-1605 https://doi.org/10.1080/03610929008830279
  15. Kang, S. G., Kim, D. H. and Lee, W. D. (2004). Noninformative priors for the ratio of parameters in inverse Gaussian distribution, The Korean Journal of Applied Statistics, 17, 49-60
  16. Mudholkar, G. and Natarajan, R. (2002). The inverse Gaussian models: Analogues of symmetry, skewness and kurtosis, Annals of the Institute Statistical thematics, 54, 138-154 https://doi.org/10.1023/A:1016173923461
  17. Mukerjee, R. and Dey, D. K. (1993). Frequentist validity of posterior quantiles in the presence of a nuisance parameter: Higher order asymptotics, Biometrika, 80, 499-505 https://doi.org/10.1093/biomet/80.3.499
  18. Mukerjee, R. and Ghosh, M. (1997). Second order probability matching priors, Biometrika, 84, 970-975 https://doi.org/10.1093/biomet/84.4.970
  19. Seshadri, V. (1999). The Inverse Gaussian Distribution: Statistical Theory and Applications, Springer, New York
  20. Stein, C. (1985). On the coverage probability of confidence sets based on a prior distribution, In Sequential Methods in Statistics, Banach Center Publications, 16, 485-514 https://doi.org/10.4064/-16-1-485-514
  21. Tibshirani, R. (1989). Noninformative priors for one parameter of many, Biometrika, 76, 604-608 https://doi.org/10.1093/biomet/76.3.604
  22. Tweedie, M. C. K. (1957a). Statistical properties of inverse Gaussian distributions I,The Annals of Mathematical Statistics, 28, 362-377 https://doi.org/10.1214/aoms/1177706964
  23. Tweedie, M. C. K. (1957b). Statistical properties of inverse Gaussian distributions II, The Annals of Mathematical Statistics, 28, 696-705 https://doi.org/10.1214/aoms/1177706881
  24. Welch, B. L. and Peers, H. W. (1963). On formulae for confidence points based on integrals of weighted likelihoods, Journal of the Royal Statistical Society, Serise B, 25, 318-329
  25. Whitmore, G. A. (1979). An inverse Gaussian model for labour turnover, Journal of the Royal Statistical Society, Series A, 142, 468-478 https://doi.org/10.2307/2982553