Yahav, I., T. Lotze, and G. Shmueli, "Algorithm Combination for Improved Detection in Biosurveillance", Infectious Disease Informatics and Biosurveillance: Integrated Series in Information Systems, 1, vol. 27: Springer, pp. 173-189, 2011. 143493_1_En_8_Chapter_OnlinePDF.pdf (1.55 MB)

Yahav, I., and G. Shmueli, "Algorithm Combination for Improved Performance in Biosurveillance Systems", Intelligence and Security Informatics: Biosurveillance, vol. 4506, pp. 91-102, 2007.

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.

Yahav, I., and G. Shmueli, An Elegant Method for Generating Multivariate Poisson Data, 10/2007.

Yahav, I., and G. Shmueli, "Evaluating Directionally-Sensitive Multivariate Control Charts with an Application to Biosurvelliance", Quality and Reliability Engineering International, vol. 30, issue 2, pp. 159-179, 2014. Manuscript (732.57 KB)

Yahav, I., and G. Shmueli, "Evaluating Directionally-Sensitive Multivariate Control Charts with an Application to Biosurveillance", Working Paper RHS 06-059: Smith School of Business, University of Maryland, 2007.

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.

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.

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.

Yahav, I., and G. Shmueli, "Outcomes Matter: Estimating Pre-Transplant Survival Rates of Kidney-Transplant Patients Using Simulation-Based Propensity Scores", Working Paper RHS 06-137: Smith School of Business, University of Maryland, 2011.

Yahav, I., and G. Shmueli, "Outcomes matter: estimating pre-transplant survival rates of kidney-transplant patients using simulator-based propensity scores", Annals of Operations Research, vol. 216, issue 1, pp. 101-128, 2014. lifetime_r2.pdf (924.59 KB)

Yahav, I., and G. Shmueli, "Predicting Potential Survival Rates of Kidney Transplant Candidates From Databases With Existing Allocation Policies", 5th INFORMS Workshop on Data Mining and Healh Informatics, Austin, TX, 05/11/2010. INFORMS 2010 DMHI.pdf (123.33 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)

Shmueli, G., T. Lotze, and I. Yahav, "Simulating Multivariate Syndromic Time Series and Outbreak Signatures", Working Paper RHS-06-054: Smith School of Business, University of Maryland, 2007.

Jank, W., G. Shmueli, M. Dass, I. Yahav, and S. Zhang, "Statistical Challenges in eCommerce: Modeling Dynamic and Networked Data", Tutorials in Operations Research: INFORMS, 2008. INFORMS Tutorials-2008-CD-chapter03.pdf (711.96 KB)

Yahav, I., G. Shmueli, and D. Mani, "A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Big Data", MIS Quarterly, vol. 40, issue 4, pp. 819-848, 2016.

Yahav, I., G. Shmueli, and D. Mani, "A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Big Data", MIS Quarterly, vol. 40, issue 4, pp. 819-848, 2016.