Bibliography

Found 164 results
Title Type [ Year(Desc)]
2008
Rettinger, F., W. Jank, G. Tutz, and G. Shmueli, "Smoothing Sparse and Unevenly-Sampled Curves using Semiparametric Mixed Models: An Application to Online Auctions", Journal of The Royal Statistical Society, Series C (Applied Statistics), vol. 57, issue 2, pp. 127-148, 2008. PDF icon JRSSC.57.2 (2008) 127-148.pdf (1.39 MB)
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. PDF icon INFORMS Tutorials-2008-CD-chapter03.pdf (711.96 KB)
Shmueli, G., "Statistical Inference with Large (eCommerce) Datasets", Working Paper RHS 06-61: Smith School of Business, University of Maryland, 2008.
Jank, W., and G. Shmueli, "Statistical Methods in eCommerce Research", Statistics in Practice: John Wiley & Sons, 2008.
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)
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)
2009
Shmueli, G., and O. Koppius, "The Challenge of Prediction in Information Systems Research", Working Paper (RHS 06-058) : Smith School of Business, University of Maryland, 2009.
Shmueli, G., and O. Koppius, "The Challenge of Prediction in Information Systems Research", Working Paper RHS 06-152: Smith School of Business, University of Maryland, 2009.
Shmueli, G., N. R. Patel, and P. C. Bruce, Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner [Korean Edition]: SciTech, 2009.
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.
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. PDF icon IJF2009 ForecastingBiosurveillance.pdf (2.19 MB)
Kenett, R. S., and G. Shmueli, "On Information Quality", Working Paper (RHS 06-100) Smith School of Business, University of Maryland,, 2009.
Shmueli, G., and W. Jank, "Modeling Dynamics in Online Auctions: A Modern Statistical Approach", Economics, Information Systems and Electronic Commerce: Empirical Research, Armonk, NY, M. E. Sharpe, pp. 157-180, 2009.
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. PDF icon SellersAndShmueliForIWSM2009-1.pdf (161.9 KB)
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., "To Explain or To Predict?", Working Paper (RHS 06-099) Smith School of Business, University of Maryland, 2009.
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.
2010
Sellers, K. F., and G. Shmueli, "Data Dispersion: Now You See it... Now You Don't", Working Paper RHS 06-122: Smith School of Business, University of Maryland, 2010.
Shmueli, G., N. R. Patel, and P. C. Bruce, Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, 2, New Jersey, John Wiley & Sons, 2010.
Dass, M., W. Jank, and G. Shmueli, "Dynamic Price Forecasting In Simultaneous Online Art Auctions", Marketing Intelligent Systems Using Soft Computing: Managerial and Research Applications, no. 258: Springer, pp. 417-445, 2010. PDF icon Casillas Martinez-Lopez 2010 book chapter.pdf (1.74 MB)

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