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題名 含外生多變數之時間數列門檻模式模型分析與預測
Constructing Threshold Model with Exogenous Variables and its Forecasting作者 王治鈞
Wang, Jhih Jyun貢獻者 吳柏林
Wu, Berlin
王治鈞
Wang, Jhih Jyun關鍵詞 外生多變數
時間數列
門檻模式
預測
Exogenous variables
Time series
Threshold model
Forecasting日期 2019 上傳時間 3-Aug-2020 17:57:26 (UTC+8) 摘要 研究目的: 探討含外生變數之時間數列門檻模式及其應用。 研究方法: 利用隱性變數找出模型之門檻值，並考慮系統內能變化修正預測。 研究發現: 含外生多變數之模糊時間數列門檻模式模型分析與預測。 研究創新: 提出以含外生多變數之門檻模式架構方法。 研究價值: 提出用模糊熵來做預測修正，增加預測之準確度。 研究結論: 本研究建構之模式，均優於傳統的模式分析與預測。
Research Objectives: Exploring the threshold model with exogenous variables and its application. Research Methods: Use implicit variables to find the threshold of the model, and consider the system internal energy change correction prediction. Research Findings: Analysis and Forecasting of threshold model of fuzzy time series with multivariate. Research Innovations: Proposing a threshold architecture method with multivariate. Research Value: Propose to use entropy to make prediction corrections and increase the accuracy of predictions.參考文獻 [1]. 吳柏林(1995) 時間數列分析導論。台北：華泰書局。[2]. 吳柏林 (2005) 模糊統計導論, 方法與應用. 台北：五南書局[3]. 楊奕農(2009) 時間序列分析：經濟與財務上之應用。台北，雙葉書廊。[4]. Kumar K and Wu B (2001). Detection of change points in time series analysis with fuzzy statistics, International Journal of Systems Science, Vol.32, No.9, pp1185-1192.[5]. Hansen, Bruce E. (1999). Testing for Linearity, Journal of Economic Surveys, Vol.13, No.5, pp551-576.[6]. Tong H. and Lim K. S. (1980), Threshold Autoregressive, Limit Cycles and Cyclical Data (with Discussion), Journal of the Royal Statistical Society. Series B, Vol.42, No.3, pp245-292.[7]. Subba Rao T. and Gabr M. (1980). A test for linearity of stationary time series analysis, Journal of Time Series Analysis , Vol.1, No.1, pp145-158.[8]. Haggan V. and Ozaki T. (1980). Amplitude-dependent Exponential AR Model Fitting for Non-linear Random Vibrations, in Time Series, (O. D. Anderson ed.), North-Holland, Amsterdam.[9]. Bai Jushan and Pierre Perron (2003). Computation and Analysis of Multiple Structural-Change Models, Journal of Applied Econometrics, Vol.18, No.1, pp1–22.[10]. Zhou H. D. (2005). Nonlinearity or structural break? - data mining in evolving financial data sets from a Bayesian model combination perspective, Proceedings of the 38th Hawaii International Conference on System Sciences[11]. Tsay Ruey S. (1989). Testing and Modeling Threshold Autoregressive Processes, Journal of the American Statistical Association, Vol.84, No.405, pp231-240.[12]. Hansen, Bruce E. (1999). Testing for Linearity, Journal of Economic Surveys, Vol.13, No.5, pp551-576..[13]. Chia-Lin Chang (2009). A Panel Threshold Model of Tourism Specialization and Economic Development, International Journal of Intelligent Technologies and Applied Statistics, pp. 159-186[14]. Qunyong Wang (2015). Fixed-effect panel threshold model using Stata, The Stata Journal (2015) 15, Number 1, pp. 121-134[15]. Henk A Tennekes (2016). A Critical Appraisal of the Threshold of Toxicity Model for NonCarcinogens, Journal of r uoJ Environmental & Analytical Toxicology[16]. Arastoo Bozorgi (2016). A community-based algorithm for influence maximization problem under the linear threshold model, Information Processing & Management Vol.52, Issue 6, November 2016, pp1188-1199[17]. Klaus K.Holst (2016). The liability threshold model for censored twin data, Computational Statistics & Data Analysis, Vol.93, January 2016, pp324-335 描述 碩士
國立政治大學
應用數學系
105751010資料來源 http://thesis.lib.nccu.edu.tw/record/#G0105751010 資料類型 thesis dc.contributor.advisor 吳柏林 zh_TW dc.contributor.advisor Wu, Berlin en_US dc.contributor.author (Authors) 王治鈞 zh_TW dc.contributor.author (Authors) Wang, Jhih Jyun en_US dc.creator (作者) 王治鈞 zh_TW dc.creator (作者) Wang, Jhih Jyun en_US dc.date (日期) 2019 en_US dc.date.accessioned 3-Aug-2020 17:57:26 (UTC+8) - dc.date.available 3-Aug-2020 17:57:26 (UTC+8) - dc.date.issued (上傳時間) 3-Aug-2020 17:57:26 (UTC+8) - dc.identifier (Other Identifiers) G0105751010 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/131106 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 應用數學系 zh_TW dc.description (描述) 105751010 zh_TW dc.description.abstract (摘要) 研究目的: 探討含外生變數之時間數列門檻模式及其應用。 研究方法: 利用隱性變數找出模型之門檻值，並考慮系統內能變化修正預測。 研究發現: 含外生多變數之模糊時間數列門檻模式模型分析與預測。 研究創新: 提出以含外生多變數之門檻模式架構方法。 研究價值: 提出用模糊熵來做預測修正，增加預測之準確度。 研究結論: 本研究建構之模式，均優於傳統的模式分析與預測。 zh_TW dc.description.abstract (摘要) Research Objectives: Exploring the threshold model with exogenous variables and its application. Research Methods: Use implicit variables to find the threshold of the model, and consider the system internal energy change correction prediction. Research Findings: Analysis and Forecasting of threshold model of fuzzy time series with multivariate. Research Innovations: Proposing a threshold architecture method with multivariate. Research Value: Propose to use entropy to make prediction corrections and increase the accuracy of predictions. en_US dc.description.tableofcontents 1. 前言 12. 研究理論與方法 42.1 含外生多變數之門檻自迴歸模型 42.2 隱性變數的門檻設定 92.3 模式的比較 112.4 模式建構的程序 132.5 預測的修正—應用熵進行優質預測 143. 實證分析 153.1 建立含外生變數之台股指數門檻模式 153.2 預測與修正 233.3 模型的效率性 273.4 分析與討論 364. 結論 375. 參考文獻 38 zh_TW dc.format.extent 1091907 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0105751010 en_US dc.subject (關鍵詞) 外生多變數 zh_TW dc.subject (關鍵詞) 時間數列 zh_TW dc.subject (關鍵詞) 門檻模式 zh_TW dc.subject (關鍵詞) 預測 zh_TW dc.subject (關鍵詞) Exogenous variables en_US dc.subject (關鍵詞) Time series en_US dc.subject (關鍵詞) Threshold model en_US dc.subject (關鍵詞) Forecasting en_US dc.title (題名) 含外生多變數之時間數列門檻模式模型分析與預測 zh_TW dc.title (題名) Constructing Threshold Model with Exogenous Variables and its Forecasting en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1]. 吳柏林(1995) 時間數列分析導論。台北：華泰書局。[2]. 吳柏林 (2005) 模糊統計導論, 方法與應用. 台北：五南書局[3]. 楊奕農(2009) 時間序列分析：經濟與財務上之應用。台北，雙葉書廊。[4]. Kumar K and Wu B (2001). Detection of change points in time series analysis with fuzzy statistics, International Journal of Systems Science, Vol.32, No.9, pp1185-1192.[5]. Hansen, Bruce E. (1999). Testing for Linearity, Journal of Economic Surveys, Vol.13, No.5, pp551-576.[6]. Tong H. and Lim K. S. (1980), Threshold Autoregressive, Limit Cycles and Cyclical Data (with Discussion), Journal of the Royal Statistical Society. Series B, Vol.42, No.3, pp245-292.[7]. Subba Rao T. and Gabr M. (1980). A test for linearity of stationary time series analysis, Journal of Time Series Analysis , Vol.1, No.1, pp145-158.[8]. Haggan V. and Ozaki T. (1980). Amplitude-dependent Exponential AR Model Fitting for Non-linear Random Vibrations, in Time Series, (O. D. Anderson ed.), North-Holland, Amsterdam.[9]. Bai Jushan and Pierre Perron (2003). Computation and Analysis of Multiple Structural-Change Models, Journal of Applied Econometrics, Vol.18, No.1, pp1–22.[10]. Zhou H. D. (2005). Nonlinearity or structural break? - data mining in evolving financial data sets from a Bayesian model combination perspective, Proceedings of the 38th Hawaii International Conference on System Sciences[11]. Tsay Ruey S. (1989). Testing and Modeling Threshold Autoregressive Processes, Journal of the American Statistical Association, Vol.84, No.405, pp231-240.[12]. Hansen, Bruce E. (1999). Testing for Linearity, Journal of Economic Surveys, Vol.13, No.5, pp551-576..[13]. Chia-Lin Chang (2009). A Panel Threshold Model of Tourism Specialization and Economic Development, International Journal of Intelligent Technologies and Applied Statistics, pp. 159-186[14]. Qunyong Wang (2015). Fixed-effect panel threshold model using Stata, The Stata Journal (2015) 15, Number 1, pp. 121-134[15]. Henk A Tennekes (2016). A Critical Appraisal of the Threshold of Toxicity Model for NonCarcinogens, Journal of r uoJ Environmental & Analytical Toxicology[16]. Arastoo Bozorgi (2016). A community-based algorithm for influence maximization problem under the linear threshold model, Information Processing & Management Vol.52, Issue 6, November 2016, pp1188-1199[17]. Klaus K.Holst (2016). The liability threshold model for censored twin data, Computational Statistics & Data Analysis, Vol.93, January 2016, pp324-335 zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202000969 en_US
