Jank, W., G. Shmueli, S. Wang, and P. Smith, "Modeling Price Dynamics in eBay Auctions Using Principal Differential Analysis", Working Paper RHS 06-052: Smith School of Business, University of Maryland, 2006.

Jank, W., and G. Shmueli, "Modeling Online Auctions", Statistics in Practice: John Wiley & Sons, 2010.

Jank, W., and G. Shmueli, "Functional Data Analysis in Electronic Commerce Research", Statistical Science, vol. 21, issue 2, pp. 155-166, 2006.

Kadane, J. B., G. Shmueli, T. P. Minka, S. Borle, and P. Boatwright, "Conjugate Analysis of the Conway-Maxwell-Poisson Distribution", Bayesian Analysis, vol. 1, issue 2, pp. 363-374, 2006. kadane363-374.pdf (183.73 KB)

Kadane, J. B., R. Krishnan, and G. Shmueli, "A Data Disclosure Policy for Count Data Based on the COM-Poisson Distribution", Management Science, vol. 52, issue 10, pp. 1610-1617, 2006. Manuscript (136.11 KB)

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.

Kenett, R. S., and G. Shmueli, "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. 11-19, 2016.

Kenett, R. S., and G. Shmueli, "On Information Quality", JRSS A, vol. 177, issue 1, pp. 3-27, 2014. Kenett Shumeli JRSSA 2014.pdf (689.6 KB)

Kenett, R. S., and G. Shmueli, "From Quality to Information Quality in Official Statistics", Journal of Official Statistics, vol. 32, issue 4, pp. 1–19, 2016.

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.

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)