Evolutionary Statistical Procedures
An Evolutionary Computation Approach to Statistical Procedures Designs and Applications
(Sprache: Englisch)
This book offers a solid introduction to evolutionary computation for use in applied statistics research. It guides readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods.
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Produktinformationen zu „Evolutionary Statistical Procedures “
This book offers a solid introduction to evolutionary computation for use in applied statistics research. It guides readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods.
Klappentext zu „Evolutionary Statistical Procedures “
The proposed text offers a solid introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is in the process of solving increasingly complex problems in high dimensions and its methodology is now being generalized to parameters whose estimators do not follow mathematically simple distributions. Many of these challenges involve optimizing functions for which analytic solutions are not feasible. Evolutionary algorithms present a powerful and easily understood means of approximating the optimum value in a variety of settings. The proposed text seeks to guide readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods (including both stand-alone evolutionary algorithms and hybrid methods).
Inhaltsverzeichnis zu „Evolutionary Statistical Procedures “
Introduction.- Evolutionary Computation.- Evolving Regression Models.- Time Series Linear and Nonlinear Models.- Design of Experiments.- Outliers.- Cluster Analysis.
Autoren-Porträt von Roberto Baragona, Francesco Battaglia, Irene Poli
Roberto Baragona received the 'laurea' in Mathematics from Sapienza University of Rome, Italy, in 1972. He is Professor of Data Analysis at Sapienza University. His main research interests are in time series analysis and multivariate statistics with special stress on Meta heuristic methods. Referee for several international journals and associate editor of Statistical Methods and Applications.Professor of Statistical Forecasting at Sapienza University of Rome. He taught at the University of Cagliari and at the Italian Public Administration School, and visited several European universities. Formerly Head of the Department of Statistics of Sapienza, and head of the Time Series Analysis Group of the Italian Statistical Society. Editor-in-chief of Statistical Methods and Applications.
Irene Poli is Professor of Statistics at Ca' Foscari University of Venice, and Director of the European Centre for Living Technology (ECLT, www.ecltech.org). Her current research involves developing statistical procedures for high dimensional data and deriving evolutionary experimental designs and multiobjective optimizations mainly for biochemical problems. She is Fellow of the New York Academy of Science, of the Royal Statistical Society, the Bernoulli Society, and member of the Italian Statistical Society.
Bibliographische Angaben
- Autoren: Roberto Baragona , Francesco Battaglia , Irene Poli
- 2010, XII, 276 Seiten, Masse: 16 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3642162177
- ISBN-13: 9783642162176
- Erscheinungsdatum: 05.01.2011
Sprache:
Englisch
Rezension zu „Evolutionary Statistical Procedures “
From the reviews:"The monograph under review is ... to provide a sort of guide through the world of evolutionary computation for optimization problems in statistics and related implementation issues in a variety of applications. It represents a comprehensive reference work for advanced graduate students and researchers working in the rich field at the intersection between statistics, evolutionary computation, and computer science. ... It is self-contained, each chapter is nicely introduced by a summary of the main contents and a comprehensive list of references is provided." (Marcello Sanguineti, Mathematical Reviews, Issue 2012 d)
Pressezitat
From the book reviews:"After the introductory Chapter 1, in Chapter 2, a detailed review of evolutionary computation is presented. Chapters 3-7 then discuss applications in regression, time series, design of experiments, outlier detection, and cluster analysis. Evolutionary techniques have been successfully used to solve optimization problems in several challenging applications, consequently this book may be useful to many applied statisticians." (Snigdhansu Chatterjee, Technometrics, Vol. 54 (4), November, 2012)
"The monograph under review is ... to provide a sort of guide through the world of evolutionary computation for optimization problems in statistics and related implementation issues in a variety of applications. It represents a comprehensive reference work for advanced graduate students and researchers working in the rich field at the intersection between statistics, evolutionary computation, and computer science. ... It is self-contained, each chapter is nicely introduced by a summary of the main contents and a comprehensive list of references is provided." (Marcello Sanguineti, Mathematical Reviews, Issue 2012 d)
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