Asymptotic Efficiency of Maximum Likelihood Estimation in Face Tracking Model Identification
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概要
- 論文の詳細を見る
This paper discusses the asymptotic efficiency of the maximum likelihood estimation (MLE) when the fece tracking model is specified as vector autoregression (VAR). When the size of the data vector in VAR is enlarged a little, the asymptotic distributions of the estimates by MLE become too wide to satisfy the precision requirement. Consequently, it is necessary to largely increase the quantity of the tested data for shortening the asymptotic distributions and obtaining the suitable estimates. In this paper, we give an explanation of this phenomenon and suggest user to avoid using a very long-term MLE to obtain the estimates of VAR in large size in face tracking.
- 社団法人電子情報通信学会の論文
- 2007-02-16
著者
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Lu Xin
Department Of Chemistry Wuhan University
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Nishiyama Kiyoshi
Department Computer And Information Science Iwate University
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Lu Xin
Iwate Univ. Iwate Jpn
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Nishiyama Kiyoshi
Iwate Univ. Iwate Jpn
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