Maximum likelihood estimates of incorrect Markov models for time series and the derivation of AIC
Maximum likelihood estimates of incorrect Markov models for time series and the derivation of AIC
复制标题
时间序列错误马尔可夫模型的最大似然估计和 AIC 的推导
DOI：
10.2307/3212924
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发表时间：
1980
影响因子：
1
通讯作者：
Y. Ogata
中科院分区：
文献类型：
--
作者：
Y. Ogata
给出了马尔可夫模型或自回归模型的极大似然估计量在真实分布不属于假设参数族时的渐近性质。本文回顾了赤池信息准则的推导过程。
The asymptotic behavior of the maximum likelihood estimators of Markov models or autoregressive models are given when the true distribution is not a member of the assumed parametric family. The derivation of Akaike's Information Criterion is reviewed for this case.