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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/95646

    Title: Bayesian Estimation of Periodicities
    Authors: Yu, Gwo-Hsing;Rao, A. R.
    Contributors: 淡江大學水資源及環境工程學系
    Keywords: 水文時間序列分析;傳利葉分析;周期性;經濟度量;季節性因素;Hydrologic Time Series Analysis;Fourier Analysis;Periodicity;Econometric;Seasonal Component
    Date: 1992-05
    Issue Date: 2014-02-12 20:32:16 (UTC+8)
    Abstract: In hydrologic time series analysis, the seasonal component is estimated by using averages of monthly values or by Fourier analysis. Useful as these methods have been, they have not been investigated in depth. Estimation of seasonal components in econometrics, on the other hand, has received considerable attention. The main reason for this increased attention is that econometric time series are nonstationary and are often more variable and complex than hydrologic time series. Recently, Jaynes (1985) has argued that informative priors can have great effect on the estimation of seasonal components and of noise. Jaynes'(1985) method has been analyzed in this study and several properties of his estimates are discussed. The method has been applied to estimate Seasonal Components of monthly river flow series.
    Relation: Proceedings of the Sixth IAHR International Symposium on Stochastic Hydr=aulics,頁767-774
    Appears in Collections:[Graduate Institute & Department of Water Resources and Environmental Engineering] Proceeding

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