LIKELIHOOD OF A MODEL AND INFORMATION CRITERIA
LIKELIHOOD OF A MODEL AND INFORMATION CRITERIA
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DOI：
10.1016/0304-4076(81)90071-3
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发表时间：
1981-01-01
影响因子：
6.3
通讯作者：
AKAIKE, H
中科院分区：
文献类型：
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作者：
AKAIKE, H
Akaike(1977)提出了一种建立统计模型的原则，即熵最大化原则，它将任何统计活动视为最大化未来观测分布估计结果的预期熵的努力。该原理的特点是引入了熵准则和预测性观点。分布f(.)的熵。关于另一个分布g(.)由以下因素定义
Akaike (1977) introduced a principle of statistical model building, the entropy maximization principle, which regards any statistical activity as an effort to maximize the expected entropy of the resulting estimate of the distribution of a future observation. The principle is characterized by the introduction of the entropy criterion and the predictive point of view. The entropy of a distribution f (.) with respect to another distribution g (.) is defined by