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Titlebook: A Comparison of the Bayesian and Frequentist Approaches to Estimation; Francisco J. Samaniego Book 2010 Springer Science+Business Media, L

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發(fā)表于 2025-3-21 20:09:20 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱A Comparison of the Bayesian and Frequentist Approaches to Estimation
影響因子2023Francisco J. Samaniego
視頻videohttp://file.papertrans.cn/141/140299/140299.mp4
發(fā)行地址An excellent introduction to Bayesian theory and methods, while taking an impartial view of their merits relative to the alternative "classical" or "frequentist" approach.A very readable presentation
學科分類Springer Series in Statistics
圖書封面Titlebook: A Comparison of the Bayesian and Frequentist Approaches to Estimation;  Francisco J. Samaniego Book 2010 Springer Science+Business Media, L
影響因子The main theme of this monograph is “comparative statistical inference. ” While the topics covered have been carefully selected (they are, for example, restricted to pr- lems of statistical estimation), my aim is to provide ideas and examples which will assist a statistician, or a statistical practitioner, in comparing the performance one can expect from using either Bayesian or classical (aka, frequentist) solutions in - timation problems. Before investing the hours it will take to read this monograph, one might well want to know what sets it apart from other treatises on comparative inference. The two books that are closest to the present work are the well-known tomes by Barnett (1999) and Cox (2006). These books do indeed consider the c- ceptual and methodological differences between Bayesian and frequentist methods. What is largely absent from them, however, are answers to the question: “which - proach should one use in a given problem?” It is this latter issue that this monograph is intended to investigate. There are many books on Bayesian inference, including, for example, the widely used texts by Carlin and Louis (2008) and Gelman, Carlin, Stern and Rubin (2004). These books
Pindex Book 2010
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An Overview of the Bayesian Approach to Estimation,). In our previous work, we obtained this minimum variance unbiased estimator for the reliability function R(t) and proved its efficiency by comparing it with the Maximum likelihood estimator. We used variance as a measure of comparison. But variance is only a second order measure. In this paper, we
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Comparing Bayesian and Frequentist Estimators of a Scalar Parameter,he different responses and terminologies of the hazard while achieving high concentration and interest from the learner. After developing this game, the effectiveness of this gaming method is analyzed by a comparative study of text book learning and this serious game.
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Comparing Bayesian and Frequentist Estimators under Asymmetric Loss, monitor Sputnik’s transmissions. In January 1958, they were also able to receive the signals from the first American artificial satellite, Explorer-1.. Mendon?a and Coutinho can so be associated with all the people who developed Brazil’s national space research, from the very beginning.
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