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題名 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作者 譚光榮
Tan, kuang Jung貢獻者 吳柏林
Wu, Berlin
譚光榮
Tan, kuang Jung關鍵詞 時空數列
STARMA模式
自相關
預測
Weighting matrix
STARMA model
Autocorrelation
Forecast日期 1993 上傳時間 29-四月-2016 16:43:47 (UTC+8) 摘要 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.參考文獻 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 Statistics,38,l-50. 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. 描述 碩士
國立政治大學
統計學系
G80354004資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002004191 資料類型 thesis dc.contributor.advisor 吳柏林 zh_TW dc.contributor.advisor Wu, Berlin en_US dc.contributor.author (作者) 譚光榮 zh_TW dc.contributor.author (作者) Tan, kuang Jung en_US dc.creator (作者) 譚光榮 zh_TW dc.creator (作者) Tan, kuang Jung en_US dc.date (日期) 1993 en_US dc.date.accessioned 29-四月-2016 16:43:47 (UTC+8) - dc.date.available 29-四月-2016 16:43:47 (UTC+8) - dc.date.issued (上傳時間) 29-四月-2016 16:43:47 (UTC+8) - dc.identifier (其他 識別碼) B2002004191 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/89016 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 統計學系 zh_TW dc.description (描述) G80354004 zh_TW dc.description.abstract (摘要) 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。 zh_TW dc.description.abstract (摘要) 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. en_US dc.description.tableofcontents 第一章 前言‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ １ 第二章 時空數列模式 第一節 STARMA模式‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ３ 第二節 空間階數與加權矩陣‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ５ 第三章 建立時空數列模式 第一節 確認模式‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ １１ 第二節 估計參數‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ １４ 第三節 模式診斷及檢驗‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ １６ 第四章 時空數列在產銷策略之研究 第一節 實例研究‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ １８ 第二節 結果比較與分析‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ２４ 第三節 蔬菜價格與產銷策略‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ２９ 第五章 結論‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ３１ 參考文獻 ‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ３３ zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002004191 en_US dc.subject (關鍵詞) 時空數列 zh_TW dc.subject (關鍵詞) STARMA模式 zh_TW dc.subject (關鍵詞) 自相關 zh_TW dc.subject (關鍵詞) 預測 zh_TW dc.subject (關鍵詞) Weighting matrix en_US dc.subject (關鍵詞) STARMA model en_US dc.subject (關鍵詞) Autocorrelation en_US dc.subject (關鍵詞) Forecast en_US dc.title (題名) 時空數列分析在蔬菜價格變動與產銷策略之研究 zh_TW dc.title (題名) Spatial Time Series Analysis and it`s Application : A Production- Marketing Strategy for the Vegetables Price en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 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 Statistics,38,l-50. 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. zh_TW
