bayes postulate

bayes postulate的基本解释

-

贝叶斯公设

与bayes postulate相关的网络例句 [注：此内容来源于网络，仅供参考]

Chapter 4 is the central part of this dissertation, where the bayes bilateral integrated moment is established on the base of Bayes theory, downside risk and upside potential. According to the variation coefficient which is based on the M-V approach, we substitute lower partial moment for the numerator of variation coefficient, and use higher partial moment as the substitute of the denominator, then we got bilateral integrated moment. Subsequently, through Bayes method we can absorb new information, revise the return distribution from transcendental distribution to posterior distribution, so we got bayes bilateral integrated moment.

第四章是本文的核心部分，在简要介绍Bayes理论、下方风险和上行潜能的基础上，仿照来源于Markowitz的均值——方差理论的变异系数方法，以下偏矩取代其分子部分，以上行潜能取代其分母部分，设计了双侧综合矩方法，接着再引入Bayes方法，吸纳新信息，采用后验概率，设计了Bayes双侧综合矩方法，并在理论上说明了新方法的优越性。

Study is made of Bayes estimation of the error rate proportionality parameter θ in the JM model for testing software reliability,leading to the a priori,a posteriori distribution of θ and the coresponding Bayes estimates on the Bayes assumption,Jeffrey s principle and conjugate dis- tribution,together with their comparison and discussion.

讨论了软件可靠性模型——JM 模型中故障率比例参数θ的 Bayes 估计问题，分别求出了在贝叶斯假设、杰弗莱原则和共轭分布原则下参数θ的先验分布、后验分布及相应的 Bayes 估计，并对它们进行了比较和讨论。

On the basis of analyzing the classification principle of Bayesian classification model and a variant of Bayes theorem, a new classification model based on Bayes theorem, DLBAN (double-level Bayesian network augmented naive Bayes), which adds the dependence among attributes by selecting the key attributes, is proposed.

通过分析贝叶斯分类模型的分类原则以及贝叶斯定理的变异形式，提出了一种基于贝叶斯定理的新的分类模型DLBAN(double-level Bayesian network augmented naive Bayes)。该模型通过选择关键属性建立属性之间的依赖关系。

与bayes postulate相关的网络解释 [注：此内容来源于网络，仅供参考]

bayes postulate：贝叶斯公设

bayes formula 贝叶斯公式 | bayes postulate 贝叶斯公设 | bayes solution 贝叶斯解

bayes postulate：贝氏公设

贝氏方法 Bayes methods | 贝氏公设 Bayes postulate | 贝氏过程 Bayes process