
Statistical Modeling and Analysis for Complex Data Problems Softcover reprint of hardcover 1st ed. 2005 Edition
Author(s): Pierre Duchesne (Editor), Bruno Rémillard
- Publisher: Springer
- Publication Date: October 29, 2010
- Edition: Softcover reprint of hardcover 1st ed. 2005
- Language: English
- Print length: 338 pages
- ISBN-10: 144193751X
- ISBN-13: 9781441937513
Book Description
Twenty-nine authors – largely from Montreal’s GERAD Multi-University Research Center and working in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes – present survey chapters on various theoretical and applied problems. The volume treats some of today’s more complex problems from a modeling perspective and surveys the state of current research on each topic, also providing directions for further research exploration of the area. One of ten volumes marking the 25th anniversary of GERAD.
Editorial Reviews
From the Back Cover
Statistical Modeling and Analysis for Complex Data Problems Softcover reprint of hardcover 1st ed. 2005 Edition 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. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets.
The book 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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