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    National Tsing Hua University Institutional Repository > 理學院 > 統計學研究所 > 期刊論文 >  Bayesian analysis of fractionally integrated ARMA with additive noise

    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/53999

    Title: Bayesian analysis of fractionally integrated ARMA with additive noise
    Authors: Hsu NJ;Breidt FJ
    教師: 徐南蓉
    Date: 2003
    Publisher: Wiley-Blackwell
    Relation: JOURNAL OF FORECASTING,Volume: 22,Issue: 6-7,Pages: 491-514,Published: SEP-NOV 2003
    Abstract: A new sampling-based Bayesian approach for fractionally integrated autoregressive moving average (ARFIMA) processes is presented. A particular type of ARMA process is used as an approximation for the ARFIMA in a Metropolis-Hastings algorithm, and then importance sampling is used to adjust for the approximation error. This algorithm is relatively time-efficient because of fast convergence in the sampling procedures and fewer computations than competitors. Its frequentist properties are investigated through a simulation study. The performance of the posterior means is quite comparable to that of the maximum likelihood estimators for small samples, but the algorithm can be extended easily to a variety of related processes, including ARFIMA plus short-memory noise. The methodology is illustrated using the Nile River data.
    URI: http://as.wiley.com/WileyCDA/Brand/id-35.html
    Appears in Collections:[統計學研究所] 期刊論文

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