Bose, S., G. Shmueli, P. Sur, and P. Dubey, "Fitting COM-Poisson Mixtures to Bimodal Count Data", 1st International Conference on Information, Operations Management and Statistics (ICIOMS), Kuala Lumpur, Malaysia, 01/09/2013. ICIOMS 2013 Malaysia Paper ID 28.pdf (513.9 KB)

Shmueli, G., P. C. Bruce, A. K. Deokar, and N. R. Patel, Machine Learning for Business Analytics: Concepts, Techniques, and Applications in RapidMiner, 1: John Wiley & Sons, 2023.

Shmueli, G., P. C. Bruce, P. Gedeck, I. Yahav, and N. R. Patel, Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R, 2, New Jersey, John Wiley & Sons, 2023.

Shmueli, G., W. Jank, and R. Bapna, "Measuring Consumer Surplus on eBay: An Empirical Study", Working Paper RHS-06-053: Smith School of Business, University of Maryland, 2007.

Sur, P., G. Shmueli, S. Bose, and P. Dubey, "Modeling Bimodal Discrete Data Using Conway-Maxwell-Poisson Mixture Models", ArXiv (Stat): Indian School of Business and Indian Statistical Institute, 2013.

Sur, P., G. Shmueli, S. Bose, and P. Dubey, "Modeling Bimodal Discrete Data Using Conway-Maxwell-Poisson Mixture Models", Journal of Business & Economic Statistics, vol. 33, issue 3, pp. 352-365, 2015. CMP_Mixture_Final_Unblinded.pdf (1.62 MB)

Russo, R. P., G. Shmueli, W. Jank, and N. D. Shyamalkumar, "Models For Bid Arrivals and Bidder Arrivals in Online Auctions", Methods and Applications of Statistics in Business, Finance and Management Sciences, Newark, NJ, John Wiley & Sons, pp. 293-309, 2010. FinanceHandbookShmueli.pdf (445.99 KB)

Bapna, R., J. Ramprasad, G. Shmueli, and A. Umyarov, "One-Way Mirrors and Weak-Signaling in Online Dating: A Randomized Field Experiment", Management Science, vol. 62, issue 11, pp. 3100-3122, 2016.

Bapna, R., W. Jank, and G. Shmueli, "Price Formation and its Dynamics in Online Auctions", Decision Support Systems, vol. 44, pp. 641-656, 2008. DSS 2008 Price Dynamics.pdf (674.41 KB)

Bapna, R., W. Jank, and G. Shmueli, "Price Formation and its Dynamics in Online Auctions", Working Paper RHS 06-003: Smith School of Business, University of Maryland, 2004.

Sellers, K. F., S. Borle, and G. Shmueli, "Rejoinder: The COM-Poisson Model for count data: A survey of methods and applications", Applied Stochastic Models in Business and Industry, vol. 28, issue 2, pp. 128-129, 2012. REJOINDER COM-Poisson Survey Paper submitted.pdf (79.1 KB)

Shmueli, G., W. Jank, and R. Bapna, "Sampling eCommerce Data from the Web: Methodological and Practical Issues", JSM, Minneapolis, MA, Proceedings of the American Statistical Association, Statistical Computing Section [CD-ROM], 2005. JSM2005 Web_sampling .pdf (94.5 KB)

Buono, P., C. Plaisant, A. Simeone, A. Aris, B. Shneiderman, G. Shmueli, and W. Jank, "Similarity-Based Forecasting with Simultaneous Previews: A River Plot Interface for Time Series Forecasting", 11th Intl Conference on Information Visualization (InfoViz), Zurich, Switzerland, 2007.

Shmueli, G., and H. S. Burkom, "Statistical Challenges Facing Early Outbreak Detection in Biosurveillance", Technometrics (Special Issue on Anomaly Detection), vol. 52, issue 1, pp. 39-51, 2010. Previous version ("Statistical Challenges in Modern Biosurveillance") (381.03 KB) Published Version (751.05 KB)

Shmueli, G., T. P. Minka, J. B. Kadane, S. Borle, and P. Boatwright, "A Useful Distribution for Fitting Discrete Data: Revival of the COM-Poisson", Journal of The Royal Statistical Society, Series C (Applied Statistics), vol. 54, issue 1, pp. 127-142, 2005. JRSS-COM-Poisson.pdf (278.49 KB)

Shmueli, G., T. P. Minka, J. B. Kadane, S. Borle, and P. Boatwright, "A Useful Distribution for Fitting Discrete Data: Revival of the COM-Poisson", Journal of The Royal Statistical Society, Series C (Applied Statistics), vol. 54, issue 1, pp. 127-142, 2005. JRSS-COM-Poisson.pdf (278.49 KB)

Shmueli, G., T. P. Minka, J. B. Kadane, S. Borle, and P. Boatwright, "Using Computational and Mathematical Methods to Explore a New Distribution: The v-Poisson", Technical Report #740: Dept. of Statistics, Carnegie Mellon University, 2001.

Shmueli, G., T. P. Minka, J. B. Kadane, S. Borle, and P. Boatwright, "Using Computational and Mathematical Methods to Explore a New Distribution: The v-Poisson", Technical Report #740: Dept. of Statistics, Carnegie Mellon University, 2001.

Lotze, T., G. Shmueli, S. Murphy, and H. S. Burkom, "A Wavelet-based Anomaly Detector for Early Detection of Disease Outbreaks", Proceedings of the 23rd International Conference on Machine Learning (ICML), Workshop on Machine Learning Algorithms for Surveillance and Event Detection, Pittsburgh, PA, 2006.