1,884
Views
25
CrossRef citations to date
0
Altmetric
Applications and Case Studies

Scalable Bayesian Modeling, Monitoring, and Analysis of Dynamic Network Flow Data

, , , , &
Pages 519-533 | Received 17 Jul 2015, Published online: 12 Jun 2018

References

  • Agarwal, D., Agrawal, R., Khanna, R., and Kota, N. (2010), “Estimating Rates of Rare Events With Multiple Hierarchies Through Scalable Log-Linear Models,” in KDD’10 Proceedings of the 16th ACM SIGKDD, pp. 213–222.
  • Ameen, J. R. M., and Harrison, P. J. (1985), “Normal Discount Bayesian Models” (with discussion), in Bayesian Statistics (Vol. 2), eds. J. M. Bernardo, M. H. DeGroot, D. V. Lindley, and A. F. M. Smith, North-Holland, Amsterdam: Valencia University Press, pp. 271–298.
  • Anacleto, O., Queen, C., and Albers, C. J. (2013a), “Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models, Splines and Other Traffic Variables,” Australian and New Zealand Journal of Statistics, 55, 69–86.
  • ——— (2013b), “Multivariate Forecasting of Road Traffic Flows in the Presence of Heteroscedasticity and Measurement Errors,” Journal of the Royal Statistical Society, Series C, 62, 251–270.
  • Bishop, Y., Fienberg, S. E., and Holland, P. (1975), Discrete Multivariate Analysis: Theory and Practice, Cambridge, MA: The MIT Press.
  • Brandt, P. T., Williams, J. T., Fordham, B. O., and Pollins, B. (2000), “Dynamic Modeling for Persistent Event-Count Time Series,” American Journal of Political Science, 44, 823–843.
  • Congdon, P. (2000), “A Bayesian Approach to Prediction Using the Gravity Model, With an Application to Patient Flow Modeling,” Geographical Analysis, 32, 205–224.
  • Gruber, L. F., and West, M. (2016), “GPU-Accelerated Bayesian Learning in Simultaneous Graphical Dynamic Linear Models,” Bayesian Analysis, 11, 125–149.
  • ——— (2017), “Bayesian Forecasting and Scalable Multivariate Volatility Analysis Using Simultaneous Graphical Dynamic Models,” Econometrics and Statistics, 3, 3–22.
  • Harrison, P. J., and West, M. (1987), “Practical Bayesian Forecasting,” The Statistician, 36, 115–125.
  • Harvey, A. C., and Fernandes, C. (1989), “Time Series Models for Count or Qualitative Observations,” Journal of Business and Economic Statistics, 7, 409–422.
  • Jandarov, R., Haran, M., Bjornstad, O. N., and Grenfell, B. T. (2014), “Emulating a Gravity Model to Infer the Spatiotemporal Dynamics of an Infectious Disease,” Journal of the Royal Statistical Society, Series C, 63, 423–444.
  • Jansen, B. J., Spink, A., and Kathuria, V. (2007), “How to Define Searching Sessions on Web Search Engines,” in Advances in Web Mining and Web Usage Analysis: 8th International Workshop on Knowledge Discovery on the Web, WebKDD 2006 (Lecture Notes in Computer Science), eds. O. Nasraoui, M. Spiliopoulou, J. Srivastava, B. Mobasher, and B. Masand, New York: Springer, pp. 92–109.
  • Koren, R., Bell, R., and Volinsky, C. (2009), “Matrix Factorization Techniques for Recommender Systems,” Computer, 8, 30–37.
  • Nakajima, J., and West, M. (2013a), “Bayesian Analysis of Latent Threshold Dynamic Models,” Journal of Business & Economic Statistics, 31, 151–164.
  • ——— (2013b), “Bayesian Dynamic Factor Models: Latent Threshold Approach,” Journal of Financial Econometrics, 11, 116–153.
  • ——— (2015), “Dynamic Network Signal Processing Using Latent Threshold Models,” Digital Signal Processing, 47, 6–15.
  • Pang, B., and Lee, L. (2008), “Opinion Mining and Sentiment Analysis,” Foundations and Trends in Information Retrieval, 2, 1–135.
  • Prado, R., and West, M. (2010), Time Series: Modeling, Computation and Inference, Boca Raton, FL: Chapman & Hall/CRC Press.
  • Qiu, F., Liu, Z., and Cho, J. (2005), “Analysis of User Web Traffic With a Focus on Search Activities,” in Proceedings of the Eighth International Workshop on the Web & Databases (WebDB 2005), pp. 103–108.
  • Queen, C. M., and Albers, C. J. (2009), “Intervention and Causality: Forecasting Traffic Flows Using a Dynamic Bayesian Network,” Journal of the American Statistical Association, 104, 669–681.
  • Quintana, J. M., and West, M. (1987), “An Analysis of International Exchange Rates Using Multivariate DLMs,” The Statistician, 36, 275–281.
  • Sen, A., and Smith, T. (1995), Gravity Models of Spatial Interaction Behavior, New York: Springer.
  • Silverstein, C., Marais, H., Henzinger, M., and Moricz, M. (1999), “Analysis of a Very Large Web Search Engine Query Log,” SIGIR Forum, 33, 6–12.
  • Smith, J. Q. (1979), “A Generalization of the Bayesian Steady Forecasting Model,” Journal of the Royal Statistical Society, Series B, 41, 375–387.
  • Soriano, J., Au, T., and Banks, D. (2013), “Text Mining in Computational Advertising,” Statistical Analysis and Data Mining, 6, 273–285.
  • Taddy, M. (2013), “Multinomial Inverse Regression for Text Analysis,” Journal of the American Statistical Association, 108, 755–770.
  • Tebaldi, C., and West, M. (1998), “Bayesian Inference on Network Traffic Using Link Count Data” (with discussion), Journal of the American Statistical Association, 93, 557–576.
  • Tebaldi, C., West, M., and Karr, A. F. (2002), “Statistical Analyses of Freeway Traffic Flows,” Journal of Forecasting, 21, 39–68.
  • Vallis, O., Hochenbaum, J., and Kejariwal, A. (2014), “A Novel Technique for Long-Term Anomaly Detection in the Cloud,” in 6th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 14), available at https://www.usenix.org/conference/hotcloud14/workshop-program/presentation/vallis.
  • West, M. (1986), “Bayesian Model Monitoring,” Journal of the Royal Statistical Society, Series B, 48, 70–78.
  • ——— (1994), “Statistical Inference for Gravity Models in Transportation Flow Forecasting,” Discussion Paper 94-20, Institute of Statistics & Decision Sciences, Duke University (June 1994); and NISS Technical Report #60, US National Institute of Statistical Sciences.
  • West, M., and Harrison, P. J. (1986), “Monitoring and Adaptation in Bayesian Forecasting Models,” Journal of the American Statistical Association, 81, 741–750.
  • ——— (1989a), Bayesian Forecasting & Dynamic Models (1st ed.), New York: Springer.
  • ——— (1989b), “Subjective Intervention in Formal Models,” Journal of Forecasting, 8, 33–53.
  • ——— (1997), Bayesian Forecasting and Dynamic Models (2nd ed.), New York: Springer.
  • Zhao, Z. Y., Xie, M., and West, M. (2016), “Dynamic Dependence Networks: Financial Time Series Forecasting & Portfolio Decisions” (with discussion), Applied Stochastic Models in Business and Industry, 33, 311–332.
  • Zhou, X., Nakajima, J., and West, M. (2014), “Bayesian Forecasting and Portfolio Decisions Using Dynamic Dependent Sparse Factor Models,” International Journal of Forecasting, 30, 963–980.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.