Overview
- Real-world applications to reliability and inference, data mining, bioinformatics, lifetime data, and neural networks
- New results are emphasized with potential for solving real-world problems
- For a broad audience of graduate students, researchers, and practitioners in statistics, mathematics, engineering, economics, social science, bioengineering, and bioscience
- Accessible to graduate students, yet also of interest to experts
- Includes supplementary material: sn.pub/extras
Part of the book series: Statistics for Industry and Technology (SIT)
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About this book
An outgrowth of the 12th International Conference on Applied Stochastic Models and Data Analysis, this book is a collection of invited chapters presenting recent developments in the field of data analysis, with applications to reliability and inference, data mining, bioinformatics, lifetime data, and neural networks.
Emphasized throughout the volume are new methods with the potential for solving real-world problems in various areas, including data mining and text mining, information theory and statistical applications, asymptotic behaviour of stochastic processes and random fields, bioinformatics and Markov chains, life table data, survival analysis, and risk in household insurance, neural networks and self-organizing maps, parametric and nonparametric statistics, and statistical theory and methods.
Advances in Data Analysis is a useful reference for graduate students, researchers, and practitioners in statistics, mathematics, engineering, economics, social science, bioengineering, and bioscience.
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Keywords
Table of contents (29 chapters)
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Part I Data Mining and Text Mining
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Part II Information Theory and Statistical Applications
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Part III Asymptotic Behaviour of Stochastic Processes and Random Fields
Editors and Affiliations
Bibliographic Information
Book Title: Advances in Data Analysis
Book Subtitle: Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks
Editors: Christos H. Skiadas
Series Title: Statistics for Industry and Technology
DOI: https://doi.org/10.1007/978-0-8176-4799-5
Publisher: Birkhäuser Boston, MA
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Birkhäuser Boston 2010
Hardcover ISBN: 978-0-8176-4798-8Published: 08 December 2009
eBook ISBN: 978-0-8176-4799-5Published: 25 November 2009
Series ISSN: 2364-6241
Series E-ISSN: 2364-625X
Edition Number: 1
Number of Pages: XXIV, 364
Number of Illustrations: 68 b/w illustrations
Topics: Probability Theory and Stochastic Processes, Applications of Mathematics, Optimization, Statistical Theory and Methods, Statistics for Life Sciences, Medicine, Health Sciences, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences