Bibliography

Found 170 results
[ Title(Desc)] Type Year
Filters: Author is G Shmueli  [Clear All Filters]
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 
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.
Dillard, B. L., and G. Shmueli, "Wavelet-Based Monitoring for Disease Outbreaks and Bioterrorism: Methods and Challenges", InterStat, vol. 3, issue March, 2010.
Shmueli, G., "Wavelet-based Monitoring in Modern Biosurveillance", Working Paper RHS-06-002: Smith School of Business, University of Maryland, 2005.
Shmueli, G., and O. Koppius, "What is Predictive about Partial Least Squares?", Sixth Symposium on Statistical Challenges in eCommerce Research (SCECR), University of Texas at Austin, McCombs School of Business, TX, 05/06/2010. PDF icon Conference Paper (285.09 KB)

Pages