Bibliografía
“4.1 Seasonal Arima Models | Stat 510.” 2019. https://newonlinecourses.science.psu.edu/stat510/node/67/.
Allaire, JJ, Yihui Xie, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, Hadley Wickham, Joe Cheng, and Winston Chang. 2018. Rmarkdown: Dynamic Documents for R. https://CRAN.R-project.org/package=rmarkdown.
Anacleto, Osvaldo, Catriona Queen, and Casper J Albers. 2013. “Multivariate Forecasting of Road Traffic Flows in the Presence of Heteroscedasticity and Measurement Errors.” Journal of the Royal Statistical Society: Series C (Applied Statistics) 62 (2). Wiley Online Library: 251–70.
Armstrong, Jon Scott. 1985. Long-Range Forecasting. Wiley New York ETC.
Breiman, Leo. 2003. “Statistical Modeling: The Two Cultures.” Quality Control and Applied Statistics 48 (1). Executive Sciences Institute: 81–82.
Chatterjee, Sharmistha. 2019. “ARIMA/Sarima Vs Lstm with Ensemble Learning Insights for Time Series Data.” https://towardsdatascience.com/arima-sarima-vs-lstm-with-ensemble-learning-insights-for-time-series-data-509a5d87f20a.
Chen, Chenyi, Yin Wang, Li Li, Jianming Hu, and Zuo Zhang. 2012. “The Retrieval of Intra-Day Trend and Its Influence on Traffic Prediction.” Transportation Research Part C: Emerging Technologies 22. Elsevier: 103–18. https://www.researchgate.net/publication/235899204_The_Retrieval_of_Intra-Day_Trend_and_Its_Influence_on_Traffic_Prediction.
Chung, E, and N Rosalion. 2001. “Short Term Traffic Flow Prediction.” In AUSTRALASIAN Transport Research Forum (Atrf), 24TH, 2001, Hobart, Tasmania, Australia. https://trid.trb.org/view/712262.
CIRCULACION, DIRECCIÓN GENERAL DE GESTIÓN Y VIGILANCIA DE LA. 2018a. “Tráfico. Histórico de Datos Del Tráfico Desde 2013.” https://datos.madrid.es/sites/v/index.jsp?vgnextoid=33cb30c367e78410VgnVCM1000000b205a0aRCRD&vgnextchannel=374512b9ace9f310VgnVCM100000171f5a0aRCRD. https://datos.madrid.es/sites/v/index.jsp?vgnextoid=33cb30c367e78410VgnVCM1000000b205a0aRCRD&vgnextchannel=374512b9ace9f310VgnVCM100000171f5a0aRCRD.
———. 2018b. “Tráfico. Ubicación de Los Puntos de Medida Del Tráfico.” https://datos.madrid.es/portal/site/egob/menuitem.c05c1f754a33a9fbe4b2e4b284f1a5a0/?vgnextoid=ee941ce6ba6d3410VgnVCM1000000b205a0aRCRD&vgnextchannel=374512b9ace9f310VgnVCM100000171f5a0aRCRD. https://datos.madrid.es/portal/site/egob/menuitem.c05c1f754a33a9fbe4b2e4b284f1a5a0/?vgnextoid=ee941ce6ba6d3410VgnVCM1000000b205a0aRCRD&vgnextchannel=374512b9ace9f310VgnVCM100000171f5a0aRCRD.
Cleveland, Robert B, William S Cleveland, Jean E McRae, and Irma Terpenning. 1990. “STL: A Seasonal-Trend Decomposition.” Journal of Official Statistics 6 (1): 3–73.
Davis, Gary A, and Nancy L Nihan. 1991. “Nonparametric Regression and Short-Term Freeway Traffic Forecasting.” Journal of Transportation Engineering 117 (2). American Society of Civil Engineers: 178–88. https://www.researchgate.net/publication/240141415_Nonparametric_Regression_and_Short-Term_Freeway_Traffic_Forecasting.
Hochreiter, Sepp, and Jürgen Schmidhuber. 1997. “Long Short-Term Memory.” Neural Computation 9 (8). MIT Press: 1735–80.
Hyndman, Rob, George Athanasopoulos, Christoph Bergmeir, Gabriel Caceres, Leanne Chhay, Mitchell O’Hara-Wild, Fotios Petropoulos, Slava Razbash, Earo Wang, and Farah Yasmeen. 2018. forecast: Forecasting Functions for Time Series and Linear Models. http://pkg.robjhyndman.com/forecast.
Hyndman, Rob J, and Anne B Koehler. 2006. “Another Look at Measures of Forecast Accuracy.” International Journal of Forecasting 22 (4). Elsevier: 679–88.
Kirby, Howard R, Susan M Watson, and Mark S Dougherty. 1997. “Should We Use Neural Networks or Statistical Models for Short-Term Motorway Traffic Forecasting?” International Journal of Forecasting 13 (1). Elsevier: 43–50. docs/Should we use neural networks or statistical models for short-term motorway traffic forecasting.pdf.
Lv, Yisheng, Yanjie Duan, Wenwen Kang, Zhengxi Li, Fei-Yue Wang, and others. 2015. “Traffic Flow Prediction with Big Data: A Deep Learning Approach.” IEEE Trans. Intelligent Transportation Systems 16 (2): 865–73. docs/Traffic flow prediction with big data - A deep learning approach.pdf.
Mañas, Andrés Mañas. 2019. “Github Home Amanas.” https://github.com/amanas. https://github.com/amanas.
Moritz, Steffen, and Thomas Bartz-Beielstein. 2017. “imputeTS: Time Series Missing Value Imputation in R.” The R Journal 9 (1): 207–18. https://journal.r-project.org/archive/2017/RJ-2017-009/index.html.
Olah, Christopher. 2015. “Understanding Lstm Networks.” http://colah.github.io/posts/2015-08-Understanding-LSTMs. http://colah.github.io/posts/2015-08-Understanding-LSTMs.
Oswald, R Keith, William T Scherer, and Brian L Smith. 2000. “Traffic Flow Forecasting Using Approximate Nearest Neighbor Nonparametric Regression.” Final Project of ITS Center Project: Traffic Forecasting: Non-Parametric Regressions.
Qiao, Fengxiang, Hai Yang, and William HK Lam. 2001. “Intelligent Simulation and Prediction of Traffic Flow Dispersion.” Transportation Research Part B: Methodological 35 (9). Elsevier: 843–63.
R Core Team. 2018. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Ripley, Brian D. 2007. Pattern Recognition and Neural Networks. Cambridge university press.
Rob J Hyndman, George Athanasopoulos. 2018. “Forecasting: Principles and Practice.” https://otexts.com/fpp2/. https://otexts.com/fpp2/.
Russell, Stuart J, and Peter Norvig. 2016. Artificial Intelligence: A Modern Approach. Malaysia; Pearson Education Limited, https://www.researchgate.net/publication/30874496_Artificial_Intelligence_A_Modern_Approach.
Smith, Brian L, and Michael J Demetsky. 1997. “Traffic Flow Forecasting: Comparison of Modeling Approaches.” Journal of Transportation Engineering 123 (4). American Society of Civil Engineers: 261–66.
Stathopoulos, Anthony, and Matthew G Karlaftis. 2003. “A Multivariate State Space Approach for Urban Traffic Flow Modeling and Prediction.” Transportation Research Part C: Emerging Technologies 11 (2). Elsevier: 121–35. docs/A multivariate state space approach for urban traffic flow modeling and prediction.pdf.
Sun, Shiliang, Changshui Zhang, and Guoqiang Yu. 2006. “A Bayesian Network Approach to Traffic Flow Forecasting.” IEEE Transactions on Intelligent Transportation Systems 7 (1). IEEE: 124–32. docs/A Bayesian network approach to traffic flow forecasting.pdf.
Tebaldi, Claudia, and Mike West. 1998. “Bayesian Inference on Network Traffic Using Link Count Data.” Journal of the American Statistical Association 93 (442). Taylor & Francis Group: 557–73.
Van Lint, JWC. 2008. “Online Learning Solutions for Freeway Travel Time Prediction.” IEEE Transactions on Intelligent Transportation Systems 9 (1). IEEE: 38–47.
Vlahogianni, Eleni I, Matthew G Karlaftis, and John C Golias. 2014. “Short-Term Traffic Forecasting: Where We Are and Where We’re Going.” Transportation Research Part C: Emerging Technologies 43. Elsevier: 3–19. docs/Short-term traffic forecasting: Where we are and where we are.pdf.
Werbos, P.J. 1975. Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences. Harvard University. https://books.google.es/books?id=z81XmgEACAAJ.
Xie, Yihui. 2018. Bookdown: Authoring Books and Technical Documents with R Markdown. https://CRAN.R-project.org/package=bookdown.