@article {10.3844/jmssp.2012.296.310,
article_type = {journal},
title = {Bayesian and Maximum Likelihood Solutions:  An Asymptotic Comparison Related to Cost Function},
author = {Hadda, Mechakra and Asssia, Chadli and Naceur, Tiah},
volume = {8},
year = {2012},
month = {Jul},
pages = {296-310},
doi = {10.3844/jmssp.2012.296.310},
url = {https://thescipub.com/abstract/jmssp.2012.296.310},
abstract = {Problem statement: Wald showed that the minimax solution is the Bayesian solution with respect to the law a priori the worst. We try to establish a similar result by comparing the Bayesian solution and the solution of maximum likelihood when the parameter space is a compact metrizable group. Approach: we take as a priori law Haar measure because we reduce the problem by invariance. We construct a sequence of cost functions for which we obtain a sequence of solutions Bayesian which converges to the solution of the maximum likelihood. Results: We show that both solutions are asymptotically equal. Conclusion/Recommendation: The generalization when the parameter space is a local compact group.},
journal = {Journal of Mathematics and Statistics},
publisher = {Science Publications}
}