Constrained Bayes Estimation with Applications
Constrained Bayes Estimation with Applications
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DOI：
10.1080/01621459.1992.10475236
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发表时间：
1992-06
影响因子：
3.7
通讯作者：
M. Ghosh
中科院分区：
文献类型：
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作者：
M. Ghosh
摘要贝叶斯技术被广泛应用于复合决策问题中多个参数的同时估计。然而，通常的主要目标是产生一个参数估计的集合，其直方图在某种意义上接近于总体参数的直方图。例如，这是子组分析中的情况，其中问题不仅是估计参数向量的不同分量，而且还要识别高于特定截止点的参数和低于特定截止点的其他参数。我们在本文中提出了贝叶斯估计在一个非常一般的情况下，满足这一需要。这些估计值是通过匹配估计值直方图的前两个矩和参数直方图的前两个矩的后验期望，并在这些条件下最小化估计值和参数之间的欧几里得距离的后验期望来获得的。M的几个应用
Abstract Bayesian techniques are widely used in these days for simultaneous estimation of several parameters in compound decision problems. Often, however, the main objective is to produce an ensemble of parameter estimates whose histogram is in some sense close to the histogram of population parameters. This is for example the situation in subgroup analysis, where the problem is not only to estimate the different components of a parameter vector, but also to identify the parameters that are above, and the others that are below a certain specified cutoff point. We have proposed in this paper Bayes estimates in a very general context that meet this need. These estimates are obtained by matching the first two moments of the histogram of the estimates, and the posterior expectations of the first two moments of the histogram of the parameters, and minimizing, subject to these conditions, the posterior expectation of the Euclidean distance between the estimates and the parameters. Several applications of the m...