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- W95473696 abstract "The Bayesian Approach is explored as an alternative to the Minimax Approach used in estimating processes with continuous time parameter. The choice is obvious; Bayesian Approach is not only an alternative to the Minimax Solution. A Bayes estimator is always a function of the Minimal Sufficient Statistic, and under quite general conditions, the Bayes estimator corresponding to an arbitrary prior density function which is positive for all ���� ���� Θ is Consistent and Best Asymptotically Normal (BAN). A Bayes estimator with known prior distribution is optimum in the sense that it minimizes average loss. Its superlative quality of estimating both point and interval estimates proves its efficacy as an efficient statistical estimation criterion for continuous time parametric processes." @default.
- W95473696 created "2016-06-24" @default.
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- W95473696 date "2014-01-01" @default.
- W95473696 modified "2023-09-23" @default.
- W95473696 title "Bayesian Approach: An Efficient Statistical Estimation Criterion for Continuous Time Parametric Processes" @default.
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