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    题名: A Bayesian analysis on time series structural equation models
    作者: Wang,YF;Fan,TH
    贡献者: 統計研究所
    日期: 2011
    上传时间: 2012-03-27 19:07:34 (UTC+8)
    出版者: 國立中央大學
    摘要: Structural equation models (SEM) have been extensively used in behavioral, social, and psychological research to model relations between the latent variables and the observations. Most software packages for the fitting of SEM rely on frequentist methods. Traditional models and software are not appropriate for analysis of the dependent observations such as time-series data. In this study, a structural equation model with a time series feature is introduced. A Bayesian approach is used to solve the model with the aid of the Markov chain Monte Carlo method. Bayesian inferences as well as prediction with the proposed time series structural equation model can also reveal certain unobserved relationships among the observations. The approach is successfully employed using real Asian, American and European stock return data. (C) 2010 Elsevier B.V. All rights reserved.
    關聯: JOURNAL OF STATISTICAL PLANNING AND INFERENCE
    显示于类别:[統計研究所] 期刊論文

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