Advances in Data Analysis Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks

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
Other Authors: Skiadas, Christos H. (Editor)
Format: eBook
Language:English
Published: Boston, MA Birkhäuser 2010, 2010
Edition:1st ed. 2010
Series:Statistics for Industry and Technology
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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