Likelihood and the Bayes procedure
- 721 Downloads
In this paper the likelihood function is considered to be the primary source of the objectivity of a Bayesian method. The necessity of using the expected behavior of the likelihood function for the choice of the prior distribution is emphasized. Numerical examples, including seasonal adjustment of time series, are given to illustrate the practical utility of the common-sense approach to Bayesian statistics proposed in this paper.
KeywordsLikelihood Bayes procedure Aic Seasonal adjustment
Unable to display preview. Download preview PDF.
- Abe, K;Ito, M., Maruyama, A., Yoshikawa, J., Isukada, K. andIkegami, M. (1971).Methods of Seasonal Adjustements. Research Series No. 22., Tokyo: Economic Planning Agency Economic Research Institute (In Japanese).Google Scholar
- — (1979b). A subjective view of the Bayes procedure.Research Memo.No. 117. Tokyo: The Institute of Statistical Mathematics. Revised, February 1979.Google Scholar
- — (1979c). On the use of the predictive likelihood of a Gaussian model.Research Memo.No 159. Tokyo: The Institute of Statistical Mathematics.Google Scholar
- — (1979d). On the construction of composite time series models.Research Memo.No 161. Tokyo: The Institute of Statistical Mathematics.Google Scholar
- — (1974b/1975)The Theory of Probability, Volumes 1 and 2 New York: Wiley.Google Scholar
- Kudo, H. (1973). The duality of parameter and sample.Proceedings of the Institute of Statistical Mathematics Symposium,6, 9–15 (In Japanese).Google Scholar
- Savage, L.J. (1962). Subjective probability and statistical practice. InThe Foundations of Statistical Inference. (G.A. Barnard and D.R. Cox eds.) 9–35. London: Methuen.Google Scholar
- Tihonov, A.N. (1965). Incorrect problems of linear algebra and a stable method for their solution.Soviet Math. Dokl.,6, 988–991.Google Scholar