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- We proved that some empirical Bayes estimators are the best or the best conditional unbiased. 证明了所给出的经验贝叶斯估计量是最优或条件最优无偏预测量。
- Empirical Bayes estimation (EBE) and maximum likelihood estimation (MLE) of reliability index are given, respectively. 分别给出了系统可靠性指标的经验 Bayes 估计,极大似然估计。
- Under suitable conditions we obtained precise asymptotic behavior of linear empirical Bayes estimator and its conditional Bayes risk. 在适当条件下,证得了线性经验Bayes估计和它的条件Bayes风险的精确渐近结构。
- We consider a couple of unimodal priors on the change-point first and use ML-II approach to obtain the empirical Bayes estimators in this paper. 本文首先考量一些常用的单峰前验分布，其次使用第二型最大概似估计藉以求得经验贝氏估计量。
- Secondly, under the square loss, we construct the asymptotically optimal and admissible empirical Bayes estimator of the mean for normal distribution, theconvergence rate O(n~(-1)) is also obtained. 其次,在平方损失下构造了正态分布均值的渐近最优和可容许的经验Bayes估计,并得到了其收敛速度为O(n~(-1))。
- Empirical Bayes Estimation for Delphi Quantitative Forecasting 定量特尔斐预测的经验贝叶斯估计法
- empirical Bayes estimate 经验Bayes估计
- Empirical Bayes Estimation of Variance Components in Two-Way Classification Random Effects Model 双向分类随机效应模型中方差分量经验Bayes估计的收敛速度
- Empirical Bayes estimation of the location parameter function of one-side truncated family under PA Samples PA样本下单边截断型分布族位置参数函数的经验Bayes估计
- REPEATED DISCUSSION OF ASYMPTOTICALLY OPTIMAL AND ADMISSIBLE EMPIRICAL BAYES ESTIMATION OF EXPONENTIAL PARAMETER 指数分布族参数的渐近最优与可容许的经验Bayes估计的再探讨
- Empirical Bayes Estimation with Convergence Rates about a Class of Discrete Distribution Families 一类离散分布参数的经验Bayes估计的收敛速度
- Convergence rate of empirical Bayes estimation of measure functions for parameter in two-side truncated distribution families 一维双边截断型分布族中参数函数的经验Bayes估计及其收敛速度
- Asymptotically Optimal and Admissible Empirical Bayes Estimation of the Parameter on a Class of Special Exponential Distribution Family 一类指数分布参数的渐近最优和可容许的经验Bayes估计
- empirical Bayes' estimator 经验贝叶斯估计量
- empirical Bayes estimation 经验Bayes估计
- Next, two useful empirical Bayes models for categorical data in manufacturing are introduced. 然后我们简介可用于制程中类别资料的两个有用的经验贝氏模型。
- empirical Bayes estimator 经验Bayes估计
- Utilizing the likelihood ratio method, both Bayesian and empirical Bayes monitoring techniques are proposed as the main purpose of the paper. 利用概似比的方法，提出贝氏和经验贝氏制程监控技术来作为本篇论文的主要目的。
- In the paper, first of all, a model selection technique between two empirical Bayes models for categorical data in manufacturing is proposed. 摘要:在本篇论文中，首先我们提出一个对于制程中的类别资料在两个经验贝氏模型中的模型选取技术。
- Then an empirical Bayes approach is proposed when there are available in-control categorical data generated from the manufacturing process. 然后在可以得到制程控制下所产生的某些类别资料时，提出一个经验贝氏的方法。
