Russo, R. P., G. Shmueli, and N. D. Shyamalkumar, "Models of Bidder Activity Consistent with Self-Similar Bid Arrivals", Statistical Methods in eCommerce Research: John Wiley & Sons, 2008. RussoShmueliShyamalKumar BidderActivity-revised.pdf (242.37 KB)

Rettinger, F., W. Jank, G. Tutz, and G. Shmueli, "Smoothing Sparse and Unevenly-Sampled Curves using Semiparametric Mixed Models: An Application to Online Auctions", Journal of The Royal Statistical Society, Series C (Applied Statistics), vol. 57, issue 2, pp. 127-148, 2008. JRSSC.57.2 (2008) 127-148.pdf (1.39 MB)

Murphy, S., H. S. Burkom, and G. Shmueli, "Data Adaptive Multivariate Control Charts for Routine Health Monitoring", Syndromic Surveillance Conference (in Advances in Disease Surveillance, 1:53), 2006.

Minka, T. P., G. Shmueli, J. B. Kadane, S. Borle, and P. Boatwright, "Computing with the COM-Poisson Distribution", Technical Report #776: Dept. of Statistics, Carnegie Mellon University, 2003.

Mani, D., and G. Shmueli, Impact Assessment in Observational Studies: A Classification and Regression Tree Approach: Indian School of Business, 2013.

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.

Lotze, T., and G. Shmueli, "On the relationship between forecast accuracy and detection performance: An application to biosurveillance", 2008 IEEE Conference on Technologies for Homeland Security, Boston, MA, 2008. ieee.pdf (243.68 KB)

Lotze, T., and G. Shmueli, "Ensemble Forecasting for Disease Outbreak Detection", 23rd AAAI Conference on Artificial Intelligence (AAAI-08), Chicago, IL, 2008. AAAI7LotzeT.pdf (61 KB)

Lotze, T., S. Murphy, and G. Shmueli, "Preparing Biosurveillance Data for Classic Monitoring", Advances in Disease Surveillance, vol. 6, 2008. DataPreparation AdvDisSurv.pdf (470.11 KB)

Lotze, T., G. Shmueli, and I. Yahav, "Simulating and Evaluating Biosurveillance Datasets", Biosurveillance: Methods and Case Studies: Chapman and Hall, 2010. Book Chapter (1.93 MB)

Lotze, T., and G. Shmueli, "How does improved forecasting benefit detection? An application to biosurveillance", International Journal on Forecasting, vol. 25, pp. 467-483, 2009. IJF2009 ForecastingBiosurveillance.pdf (2.19 MB)

Lin, M., H. C. Lucas, and G. Shmueli, "Too Big To Fail: Large Samples and the P-Value Problem", Information Systems Research, vol. 24, issue 4, pp. 906-917, 2013. Article (269.29 KB)

Lin, M., H. C. Lucas, and G. Shmueli, "Too Big to Fail: Larger Samples and False Discoveries", Working Paper RHS 06-068: Smith School of Business, University of Maryland, 2009.

Kenett, R. S., and G. Shmueli, From Quality to Information Quality in Official Statistics: Indian School of Business, 04/2014.

Kenett, R. S., and G. Shmueli, "Rejoinder: On Information Quality", JRSS A, vol. 177, issue 1, pp. 35-38, 2014.

Kenett, R. S., and G. Shmueli, "On Information Quality", Working Paper RHS 06-100: Smith School of Business, University of Maryland, 2011.

Kenett, R. S., and G. Shmueli, "Rejoinder: Helping authors and reviewers ask the right questions: The InfoQ framework for reviewing applied research", Statistical Journal of the IAOS, vol. 32, issue 1, pp. 33-35, 2016.

Kenett, R. S., and G. Shmueli, Information Quality: The Potential of Data and Analytics to Generate Knowledge: John Wiley & Sons, pp. 384, 2016.

Kenett, R. S., and G. Shmueli, "A special issue on: Actual impact and future perspectives on stochastic modelling in business and industry", Applied Stochastic Models in Business and Industry, vol. 31, issue 1, pp. 1-2, 2015.

Kenett, R. S., and G. Shmueli, "On Information Quality", Working Paper (RHS 06-100) Smith School of Business, University of Maryland,, 2009.