Editors:
- One of ten volumes marking the 25th anniversary of GERAD covering most of the Center's research areas of expertise
- Examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area
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Table of contents (15 chapters)
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Front Matter
About this book
Statistical Modeling and Analysis for Complex Data Problems treats some of today’s more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors – largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.
Editors and Affiliations
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Université de Montréal and GERAD, Montréal
Pierre Duchesne
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HEC Montréal and GERAD, Montréal
Bruno RÉMillard
Bibliographic Information
Book Title: Statistical Modeling and Analysis for Complex Data Problems
Editors: Pierre Duchesne, Bruno RÉMillard
DOI: https://doi.org/10.1007/b105993
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag US 2005
Hardcover ISBN: 978-0-387-24554-6Published: 12 April 2005
Softcover ISBN: 978-1-4419-3751-3Published: 29 October 2010
eBook ISBN: 978-0-387-24555-3Published: 05 December 2005
Edition Number: 1
Number of Pages: XIV, 324
Topics: Optimization, Theory of Computation, Medicine/Public Health, general, Probability Theory and Stochastic Processes, Statistical Theory and Methods, Statistics and Computing/Statistics Programs