December 1, 1974Open Access

统计模型识别的新视角

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Abstract

本文简要回顾了时间序列分析中统计假设检验的发展历程，指出假设检验程序作为统计模型识别程序定义得不够充分。对经典的最大似然估计程序进行了回顾，并引入了为统计识别目的设计的新估计最小信息理论准则（AIC）估计（MAICE）。当存在多个竞争模型时，MAICE由模型及其参数的最大似然估计定义，该估计使得AIC达到最小，AIC定义为AIC = (-2)log－(最大似然) + 2(模型中独立调整参数的数量)。MAICE提供了一种灵活的统计模型识别程序，避免了传统假设检验程序应用中的歧义。通过一些数值实例展示了MAICE在时间序列分析中的实际应用价值。

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Hirotugu Akaike

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IEEE Transactions on Automatic Control

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The Institute of Statistical Mathematics

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Hirotugu Akaike（Sun）研究了这个问题。

www.synapsesocial.com/papers/69813150ce4d1f8e18d4e865 — DOI: https://doi.org/10.1109/tac.1974.1100705

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统计模型识别的新视角

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