Shmueli, G., R. Saha, and R. Gupta, "Industry-academia partnerships", ORMS Today (INFORMS Magazine), issue August, pp. 32-34, 2013. Industry-Academia Partnerships ORMS Today Aug 2013.pdf (1.59 MB)

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

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)

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.

Hardoon, D. R., and G. Shmueli, Getting Started with Business Analytics: Insightful Decision Making: Chapman and Hall/CRC, pp. 190, 2013.

Yahav, I., and G. Shmueli, "On Generating Multivariate Poisson Data in Management Science Applications", Applied Stochastic Models in Business and Industry, vol. 28, issue 1, pp. 91-102, 2012. Multivariate-Poisson ASMBI 2012.pdf (1.52 MB)

Yahav, I., and G. Shmueli, "On Generating Multivariate Poisson Data in Management Science Applications", Working Paper RHS 06-085: Smith School of Business, University of Maryland, 2009.

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

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, "From Quality to Information Quality in Official Statistics", Journal of Official Statistics, vol. 32, issue 4, pp. 1–19, 2016.

Shmueli, G., and I. Yahav, The Forest or the Trees? Tackling Simpson's Paradox with Classification and Regression Trees: Indian School of Business, 2014.

Shmueli, G., and I. Yahav, "The Forest or the Trees? Tackling Simpson's Paradox with Classification Trees", Production and Operations Management, vol. 27, pp. 696–716, 2018.

Jank, W., and G. Shmueli, "Forecasting Online Auctions using Dynamic Models", Data Mining for Business Applications, no. 218: IOS Press, pp. 137-148, 2010. IOS-BookChapter-Jank & Shmueli.pdf (102.47 KB)

Sellers, K. F., and G. Shmueli, "A Flexible Regression Model for Count Data", Working Paper RHS 06-060: Smith School of Business, University of Maryland, 2008.

Sellers, K. F., and G. Shmueli, "A Flexible Regression Model for Count Data", Annals of Applied Statistics, vol. 4, issue 2, pp. 943-961, 2010. Supplementary Materials (126.65 KB) AOAS COM-Regression.pdf (405.74 KB)

Jank, W., G. Shmueli, and S. Zhang, "A Flexible Model for Estimating Price Dynamics in Online Auctions", JRSS C, vol. 59, issue 5, pp. 781-804, 2010. JRSSC_2010.pdf (852.14 KB)

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)

Hyde, V., W. Jank, and G. Shmueli, "A Family of Growth Models for Representing the Price Process in Online Auctions", Statistical Methods in eCommerce Research: John Wiley & Sons, 2008. GrowthModelsFinal.pdf (994.83 KB)

Hyde, V., W. Jank, and G. Shmueli, "A Family of Growth Models for Representing the Price Evolution in Online Auctions", 9th Intl Conference on Electronic Commerce, Minneapolis, MA, 2007.

Chatla, S.B., and G. Shmueli, "An Extensive Examination of Regression Models with a Binary Outcome Variable", Journal of the Association for Information Systems, vol. 18, issue 4, pp. article 1, 2017.