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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/89016
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/89016

    Title: 時空數列分析在蔬菜價格變動與產銷策略之研究
    Spatial Time Series Analysis and it's Application : A Production- Marketing Strategy for the Vegetables Price
    Authors: 譚光榮
    Tan, kuang Jung
    Contributors: 吳柏林
    Wu, Berlin
    Tan, kuang Jung
    Keywords: 時空數列
    Weighting matrix
    STARMA model
    Date: 1993
    Issue Date: 2016-04-29 16:43:47 (UTC+8)
    Abstract: 蔬菜的供給彈性非常小,收成之後,不僅產量會決定售價的高低,同類蔬菜之間的替代效果,對於價格變化也有很大的影響力。因此若能事先預測同類蔬菜未來的價格變化,即可計劃各類蔬菜的生產量。在本篇論文中,我們試著將時空數列應用在非空間系統的經濟領域上。以臺灣地區三種常見的蔬菜為例,分別以時空數列的 STARMA 模式與單變量 ARIMA 時間數列,利用蔬菜批發價格建立模式,並比較其短期預測效果。最後,就價格變動與產銷策略之關係進行討論。
    The supply elasticity of vegetables is so small. Once the production has been known, it would reflect on the price as soon as possible. And at the same time, the substitute effect between the vegetables has also great influence on the change of the price. However, if we could forecast the variation of the vegetables price,then the production-marketing strategy would be planned in advance. In this paper, we apply the spatial time series analysis on the field of economic, which is included in the non-spatial system. An investigate about the price variation for three kinds of vegetables in Taiwan.And the comparison of short-term forecasting performance for the STARMA model and traditional ARIMA model are also made. Finally, we discuss in detail about the relationship between the change of vegetable price and production-marketing strategy.
    Reference: Ali, M.M.(1979). Analysis of stationary spatial temporal processes: estimation
    and prediction,Biometrika,66,513-518.
    Bennett, R.J. (1979). Spatial time series,Pion Lin1ited,London.
    Bennett, R.J.(1984). Advances in the analysis of spatial time series ,Spatial
    Statistics and lvlodels,235-251.
    Besag ,J. (1974). Spatial interaction and the statistical analysis of lattice
    systen1s, Journal of the Royal Statistical Society)B, 36,192-225.
    Box, G.E.P. and Jenkins, G.Iv1.(1976). Time series analysis forecasting and
    control,2nd ed.,Rolden-Day,San-Francisco.
    Cliff, A.D. and Ord, J.K.(1981). Spatial processes: models and applications,
    Pion Limited,London.
    Deutsch ,S.J. and Pfeifer, P.E.(1980a). A Three-Stage iterative procedure for
    space-tilDe modeling , Techno'metrics,22 ,35-47.
    Deutsch ,S.J. and Pfeifer, P.E. (1980b). Identification and interpretation of
    first order space-tilDe ARIv1A models 1 Technometrics, 22,397-408.
    Deutsch ,S.J. and Pfeifer, P.E.(1981). Space-Time ARIv1A modeling with
    contemporaneously correlated innovations, Techno'metrics,23, 401-409.
    Flahault ,A.,et al. (1988). IvIodelling the 1985 influenza epidemic in Frence ,
    Statistics in Medicine,7,1147-1155.
    Griffith, D.A., Raining, R.P. and Bennett, R.J. (1985). Estimating missing
    values in space-time data series, Time Series Analysis: Theory and
    Practice 6,273-296.
    Haslett, J. and Raftery, A.E.(1989). Space-Tilne modelling with long - memory
    dependence : assessing Ireland's wind power resource , Applied
    NIann,H.B. and vVald,A.(1943). On the statistical treatment of linear stochastic
    dfference equations, Econometrika, II, 173-270.
    Pfeifer, P.E. and Bodily, S.E. (1990). A Test of space-tinle ARNIA modelling
    and forcasting of hotel data, J o'Uxnal of Forecasting ,9, 255-272.
    Raftery, A.E.,Haslett, J. and NIcColI, E.(1982). ,;Vind power: A space-time
    process, Time Series Analysis: Theory and Practice 2, 191-202.
    Rogers, A.(1974). Statistical analysis of spatial dispersion: the quadrat
    method, Pion Limited,London.
    Stoffer, D.S.(1986). Estimation and identification of space-time ARNIAX
    models in the presence of n1issing data , Journal of the American Statistical
    Association, 81,762-772.
    Tjostheim, D.(1978). Statistical spatial series modelling, Adv. Appl. Frob.
    ,10, 130-154.
    Wei, Willian1 W.S.(1990). Tims series analysis: univariate and multivariate
    methods, Addison-Wesley.
    Zeger, S.L.(1985). Exploring an ozone spatial time series in the frequency
    dOlnain ,Jo'urnal of the American Statistical Associations, 80, 323-33l.
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002004191
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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