...建构其模型的，最著名的表现 是“预期效益最人化”（the maximizationof expectedutility）和“贝叶斯模型” （Bayesian models）。概率理论的产生形成了我们关『＾人脑功能的基本看法，心理 机能被假定为依据事物产生的概率及其效用而进行的运算。
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... Bayesian models: 贝氏模型 nonparametric Bayesian models: 非参数贝叶斯模型 Bayesian Models for Categorical Data: 贝叶斯模型的属性数据 ...
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Bayesian Models for Categorical Data 贝叶斯模型的属性数据
nonparametric Bayesian models 非参数贝叶斯模型
Double level Bayesian models 双层贝叶斯模型
BAYESIAN CONDITIONAL PROBABILITY MODELS 贝叶斯条件概率模型
bayesian dynamic models 贝叶斯动态模型
Bayesian learning models 贝叶斯学习模型
Bayesian harmonic models 贝叶斯谐波模型
nonlinear Bayesian dynamic models 非线性贝叶斯动态模型
bayesian dynamic linear models 贝叶斯动态线性模型
Finally, collected defect data samples are used to verify the model and the result indicated that the model is better than the common Bayesian models both in veracity and stability of prediction.
通过收集到的缺陷数据样本比较结果表明，该模型比一些常用贝叶斯模型具有更好的预测准确性和稳定性。
Bayesian model averaging was used to combine the results across models and to provide a measure of uncertainty that reflects the choice of model and the sampling variability.
贝叶斯模型平均法用来综合各模型的结果并提供一种反映模型选择和抽样变异性的不确定性度量。
It appears to be objective. But when models are built, it is almost impossible to avoid including Bayesian-style prior assumptions in them.
但是模型建立起来后，几乎不可避免地把贝叶斯的预先假定理论也纳入了模型中。
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