Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks
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The work Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks represents a distinct intellectual or artistic creation found in University of Oklahoma Libraries. This resource is a combination of several types including: Work, Language Material, Books.
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Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks
Resource Information
The work Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks represents a distinct intellectual or artistic creation found in University of Oklahoma Libraries. This resource is a combination of several types including: Work, Language Material, Books.
 Label
 Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks
 Title remainder
 Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks
 Statement of responsibility
 edited by Christos H. Skiadas
 Subject

 Mathematics
 Statistics
 Optimization
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 Mathematical statistics
 Distribution (Probability theory
 Statistics for Life Sciences, Medicine, Health Sciences
 Mathematical optimization
 Probability Theory and Stochastic Processes
 Statistical Theory and Methods
 Applications of Mathematics
 Language

 eng
 eng
 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 realworld 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 SelfOrganizing 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
 Dewey number

 003.76
 519
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsedt
 X6nb2KuxTJc
 Language note
 English
 LC call number

 QA273.A1274.9
 QA274274.9
 Literary form
 non fiction
 Nature of contents
 dictionaries
 Series statement
 Statistics for Industry and Technology,
Context
Context of Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural NetworksWork of
 Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks, edited by Christos H. Skiadas, (electronic resource)
 Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks, edited by Christos H. Skiadas, (electronic resource)
 Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks, edited by Christos H. Skiadas, (electronic resource)
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