Bibliography

Found 169 results
[ Title(Asc)] 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 
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Shmueli, G., and A. Tafti, "How to “Improve” Prediction Using Behavior Modification", International Journal on Forecasting, vol. 39, issue 2, pp. 541-555, 2023.
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, "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.
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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. PDF icon 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.
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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. PDF icon 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. PDF icon Supplementary Materials (126.65 KB)PDF icon 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. PDF icon 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. PDF icon 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. PDF icon 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.

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