Bibliography

Found 163 results
[ Title(Desc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
S
Jank, W., and G. Shmueli, "Statistical Methods in eCommerce Research", Statistics in Practice: John Wiley & Sons, 2008.
Jank, W., and G. Shmueli, "Studying Heterogeneity of Price Evolution in eBay Auctions Via Functional Clustering", Business Computing, vol. 3: Emerald, pp. 237-261, 2009.
Shmueli, G., "System-Wide Probabilities for Systems with Runs and Scans Rules", Methodology and Computing in Applied Probability, vol. 4, pp. 401-419, 2003. PDF icon Mcap_5118753.pdf (989.79 KB)
T
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. PDF icon ICML 2012 Teaching BS vs CS.pdf (413.83 KB)
Shmueli, G., "To Explain or To Predict?", Working Paper (RHS 06-099) Smith School of Business, University of Maryland, 2009.
Shmueli, G., "To Explain or To Predict?", Statistical Science, vol. 25, issue 3, pp. 289-310, 2010. PDF icon Stat Science published.pdf (293.36 KB)
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. PDF icon 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.
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., W. Jank, and V. Hyde, "Transformations for Semi-Continuous Data", Computational Statistics & Data Analysis, vol. 52, issue 8, pp. 4000-4020, 2008. PDF icon CSDA-semiContinuousData.pdf (1.51 MB)
Gupta, R., D. Mani, S. Mithas, and G. Shmueli, "Tree Matching Solution for Self-Selection in Impact Surveys", Statistical Challenges in Ecommerce Research (SCECR), Montreal, Canada, 28/06/2012. PDF icon SCECR 2012 Poster Tree Matching for Self-Selection in Impact Surveys.pdf (807.52 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.
U
Fu, J. C., G. Shmueli, and Y. M. Chang, "A Unified Markov Chain Approach for Computing the Run Length Distribution in Control Charts with Simple or Compound Rules", Statistics & Probability Letters, vol. 65, issue 4, pp. 457-466, 2003. PDF icon StatProbLettersPaper.pdf (246.79 KB)
Shmueli, G., T. P. Minka, J. B. Kadane, S. Borle, and P. Boatwright, "A Useful Distribution for Fitting Discrete Data: Revival of the COM-Poisson", Journal of The Royal Statistical Society, Series C (Applied Statistics), vol. 54, issue 1, pp. 127-142, 2005. PDF icon JRSS-COM-Poisson.pdf (278.49 KB)
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.
V
Jank, W., G. Shmueli, C. Plaisant, and B. Shneiderman, "Visualizing Functional Data with an Application to eBays Online Auctions", Handbook on Computational Statistics on Data Visualization, Heidelberg, Springer, 2008. PDF icon CSC-Visualizing-FDA.pdf (1.14 MB)
Shmueli, G., and W. Jank, "Visualizing Online Auctions", Journal of Computational and Graphical Statistics, vol. 14, issue 2, pp. 299-319, 2005. PDF icon JCGS Visualizing Online Auctions.pdf (923.45 KB)
W
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.
Shmueli, G., "Wavelet-Based Monitoring for Biosurveillance", Axioms, vol. 2, issue 3, pp. 345-370, 2013.

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