# 臺灣博碩士論文加值系統

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 對於那些要經常在尖峰時間使用高速公路的人而言, 避免不必要的擁擠以節省寶貴時間是相當重要的. 在本篇論文中, 我們將用一些統計的方法來分析高速公路的車流資料並且發展一種方法在高速公路各檢測器上預測短期的車流變化. 我們將使用考慮時間, 日期, 和上游車流量的hierarchical 迴歸模型. 我們用高速公路北部路段的車流量當作我們所要分析的資料.
 For those who usually use Freeway at peak time period, predicting the car flows at these periods and avoiding unnecessary congestion in order to save time is important. In this thesis, we want to use statistical model to analyze the freeway flow data and develop a technique in predicting short-term flow changes on sequence of detectors in a freeway network. We use hierarchical regression model which considers time of day, day of week and upstream detector flows. The data we analyze come from Taiwan Area National Freeway Bureau.
 Contents 1. Introduction 3 2. Data collection 5 2.1 Data obtaining 5 2.2 Data screening 6 2.3 Data selection 6 3. Spline function, Hierarchical regression model, and Gibbs sampler 8 3.1 Spline function 8 3.2 Hierarchical regression model 9 3.3 Gibbs sampler 13 4. Numerical results 15 5. Conclusion 19 Appendix 20 Reference 28
 Anderson, T. W. (1984), An introduction to Multivariate Statistical Analysis, 2nd edition, John Wiley & Sons.Box, G.E.P., and Tiao, G.C. (1992), Bayesian Inference in Statistical Analysis, John Wiley & Sons.Geman, S. and Geman D. (1984), ‘Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images’, IEEE, Trans. Pat. Anal. Mach. Intel. 6, 721-741.Gelfand, A. E., Hills, S. E., Racine-Poon, A., and Simth, A. F. M. (1990), ‘Illustration of Bayesian inference in normal data models using Gibbs sampling’, Journal of the American Statistical Association, vol. 85, 972—985.Gilks, W. R., Roberts, G.. O., Suhu, S. K. (1998), ‘Adaptive Markov chain Monte Carlo through regeneration’, Journal of the American Statistical Association, vol. 93, 1045-1054.Hastings, W. K. (1970), ‘Monte Carlo sampling methods using Markov chains and their applications’, Biometrika, 57, 97-109.Lindley, D.V. and Smith, A.F.M. (1972), ‘Bayes estimates for the linear model’( with discussion ), Journal of the Royal Statistical Society, Ser. B , 34, 1-41.Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H. and Teller, E. (1953), ‘Equations of state calculations by fast computing machine’, J. Chem. Phys., 21, 1087-1091.Seber, G. A. F. and Wild, C. J. (1989), Nonlinear Regression, 1st edition, John Wiley & Sons.Smith, A.F.M. (1973), ‘A general Bayesian linear model’, Journal of the Royal Statistical Society, Ser. B, 35, 67-75.Stapleton, J.H. (1995), Linear Statistical Models, 1st edition, John Wiley & Sons.Tebaldi, C., West, M. and Karr, A.F. (2002), ‘Statistical analyses of freeway traffic flows’, International Journal of Forecasting, 21, 39 — 68.Van Arem, B., Kirby, H. R., Van Der Vlist, M. J. M., Whittaker J. C. (1997), ‘Recent advances and applications in the field of short-term traffic forecasting’, International Journal of Forecasting, 13, 1 — 12.West, M. and Harrison, P.J. (1997), Bayesian Forecasting and Dynamic Models, 2nd edition, Springer-Verlag: New York.Wold, S. (1974), ‘Spline functions in data analysis’, Technometrics, 16, 1 — 11.
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 1 關於高速公路車流量問題之分析 2 計算高速公路車流量之系統模擬 3 利用資料探勘探討時間對車流量大小因素之研究-以后里收費站為例 4 韋伯隨機變數之和的分佈函數的逼近法 5 貝氏估計在時間序列上的應用 6 Copula模式之文獻回顧與應用 7 用逆高斯模型時競爭風險的估計 8 眾數型態全距之統計推論及其應用 9 類別資料的經驗貝氏製程監控技術 10 EWMA管制圖對自相關性製程的常態假設穩健性之研究 11 監控多變量製程變異性增加之EWMA管制圖 12 關於微陣列資料的前景與背景之變異數分析模型 13 用無母數迴歸法分析變數間之因果關係 14 SVM在基因選擇之研究 15 利用貝氏空間模型所做的系集預測

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