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bayesian d-optimality

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Bayesian D 最优性
Bayesian D-optimality estimates a specified set of model parameters precisely.
Bayesian D 最优性可准确估计指定的一组模型参数。
The objective function is the Bayesian D-optimality criterion.
目标函数是 Bayesian D 最优性准则。
The Bayesian D-optimality criterion is the expectation of the logarithm of the determinant of the information matrix with respect to a sample of parameter vectors that represents this prior probability distribution.
Bayesian D 最优性准则是信息矩阵对表示该先验概率分布的参数向量样本求得的行列式的对数期望值。
But at the same time, Bayesian D-optimality has the ability to estimate other, typically higher-order effects, as allowed by the run size.
但同时,Bayesian D 最优性有能力估计其他效应,通常为高阶效应(在试验规模允许的情况下 ) 。
When there are potentially active terms that are not included in the assumed model, a better approach is to specify If Possible terms and to use a Bayesian D-optimal design. Bayesian D-Optimality
若存在可能活跃的项未包含在假设模型中,更好的方法是指定"若可能"项并使用 Bayesian D 最优设计。 Bayesian D 最优性
The Bayesian D-optimality criterion is most effective when the number of runs is larger than the number of Necessary terms, but smaller than the sum of the Necessary and If Possible terms.
在试验次数大于"必需"项个数但小于"必需"项与"若可能"项个数之和的情况下,Bayesian D 最优性准则最为有效。
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Synoniemen voor bayesian d-optimality in het Engels

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