Advances in Data Analysis Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks / edited by Christos H. Skiadas.

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, an...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Skiadas, Christos H. (Editor)
Format: eBook
Language:English
Published: Boston, MA : Birkhäuser Boston : Imprint: Birkhäuser, 2010.
Edition:1st ed. 2010.
Series:Statistics for Industry and Technology,
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Description
Summary: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. The book is divided into eight major sections: * 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 * 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.
Physical Description:XXIV, 364 p. 68 illus. online resource.
ISBN:9780817647995
ISSN:2364-6241
DOI:10.1007/978-0-8176-4799-5