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., 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., and R. S. Kenett, "An Information Quality (InfoQ) Framework for Ex-Ante and Ex-Post Evaluation of Empirical Studies", Intelligent Data Analysis and Management (IDAM), Kaohsiung, Taiwan, 09/09/2013. InfoQ_IDAM_2013.pdf (179.21 KB)

Shmueli, G., N. R. Patel, and P. C. Bruce, Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner [Indian Edition], 1st edition: Wiley India, 2008.

Shmueli, G., and K. C. Lichtendahl, Jr., "Practical Time Series Forecasting with R: A Hands-On Guide", Practical Analytics: Axelrod Schnall, pp. 208, 2015.

Shmueli, G., and W. Jank, "Visualizing Online Auctions", Journal of Computational and Graphical Statistics, vol. 14, issue 2, pp. 299-319, 2005. JCGS Visualizing Online Auctions.pdf (923.45 KB)

Shmueli, G., "Practical Time Series Forecasting: A Hands-On Guide", Practical Analytics: Axelrod Schnall, 2011.

Shmueli, G., W. Jank, and V. Hyde, "Transformations for Semi-Continuous Data", Working Paper RHS 06-051: Smith School of Business, University of Maryland, 2006.

Shmueli, G., P. C. Bruce, I. Yahav, N. R. Patel, and K. C. Lichtendahl, Jr., Data Mining for Business Analytics: Concepts, Techniques, and Applications in R, 1, New Jersey, John Wiley & Sons, 2017.

Shmueli, G., and A. Cohen, "Run Related Probability Functions Applied to Sampling Inspection", Technometrics, vol. 42, issue 2, pp. 188-202, 2000. RunsTechnometrics2000.pdf (1.13 MB)

Shmueli, G., and C. Soares, "Teaching Data Mining in the Business School: Experience from Three Continents", Teaching Machine Learning Workshop, ICML, Edinburgh, Scotland, UK, June 2012. ICML 2012 Teaching BS vs CS.pdf (413.83 KB)

Shmueli, G., and O. Koppius, "Predictive vs. Explanatory Modeling in IS Research", Conference on Information Systems & Technology (Best Paper Award), Seattle, WA, 03/11/2007.

Sharma, P., M. Sarstedt, G. Shmueli, K. H. Kim, and K. O. Thiele, "PLS-based model selection: the role of alternative explanations in information systems research", Journal of the Association for Information Systems, vol. 20, issue 4, 2019.

Sharma, P., G. Shmueli, M. Sarstedt, N. Danks, and S. Ray, "Prediction-Oriented Model Selection in Partial Least Squares Path Modeling", Decision Sciences, 2019.

Sellers, K. F., and G. Shmueli, "Predicting Censored Count Data with COM-Poisson Regression", Working Paper RHS 06-129: Smith School of Business, University of Maryland, 2010.

Sellers, K. F., and G. Shmueli, "A Regression Model for Count Data with Observation-Level Dispersion", 24th International Workshop on Statistical Modelling (IWSM), Cornell University, Ithaca, NY, 20/07/2009. SellersAndShmueliForIWSM2009-1.pdf (161.9 KB)

Sellers, K. F., and G. Shmueli, "Data Dispersion: Now You See it... Now You Don't", Communications in Statistics: Theory and Methods, vol. 42, issue 17, pp. 2434-2447, 2013. SubmittedRevision.pdf (261.2 KB)

Sellers, K. F., S. Borle, and G. Shmueli, "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. 104-116, 2012. COM-Poisson Survey (581.27 KB)

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)

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)