ASA-SIAM Series on
Statistics and Applied Probability
The ASA-SIAM Series on Statistics and Applied Probability is published
jointly by the American Statistical Association and the Society for Industrial and Applied Mathematics.
The series consists of a broad spectrum of books on topics in statistics and applied probability. The
purpose of the series is to provide inexpensive, quality publications of interest to the intersecting
membership of the two societies.
Editorial Board
Martin T. Wells
Cornell University, Editor-in-Chief
H. T. Banks
North Carolina State University
Douglas M. Hawkins
University of Minnesota
Susan Holmes
Stanford University
Gan, G., Ma, C., and Wu, J., Data Clustering: Theory, Algorithms, and Applications
Hubert, L., Arabie, P., and Meulman, J., The Structural Representation of Proximity Matrices with MATLAB
Nelson, P. R., Wludyka, P. S., and Copeland, K. A. F., The Analysis of Means: A Graphical Method for
Comparing Means, Rates, and Proportions
Burdick, R. K., Borror, C. M., and Montgomery, D. C., Design and Analysis of Gauge R&R Studies: Making
Decisions with Confidence Intervals in Random and Mixed ANOVA Models
Albert, J., Bennett, J., and Cochran, J. J., eds., Anthology of Statistics in Sports
Smith, W. F., Experimental Design for Formulation
Baglivo, J. A., Mathematica Laboratories for Mathematical Statistics: Emphasizing Simulation and
Computer Intensive Methods
Lee, H. K. H., Bayesian Nonparametrics via Neural Networks
O’Gorman, T. W., Applied Adaptive Statistical Methods: Tests of Significance and Confidence Intervals
Ross, T. J., Booker, J. M., and Parkinson, W. J., eds., Fuzzy Logic and Probability Applications: Bridging the Gap
Nelson, W. B., Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other
Applications
Mason, R. L. and Young, J. C., Multivariate Statistical Process Control with Industrial Applications
Smith, P. L., A Primer for Sampling Solids, Liquids, and Gases: Based on the Seven Sampling Errors of
Pierre Gy
Meyer, M. A. and Booker, J. M., Eliciting and Analyzing Expert Judgment: A Practical Guide
Latouche, G. and Ramaswami, V., Introduction to Matrix Analytic Methods in Stochastic Modeling
Peck, R., Haugh, L., and Goodman, A., Statistical Case Studies: A Collaboration Between Academe and
Industry, Student Edition
Peck, R., Haugh, L., and Goodman, A., Statistical Case Studies: A Collaboration Between Academe and
Industry
Barlow, R., Engineering Reliability
Czitrom, V. and Spagon, P. D., Statistical Case Studies for Industrial Process Improvement
Lisa LaVange
University of North Carolina
David Madigan
Rutgers University
Mark van der Laan
University of California, Berkeley
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