Advances in data analysis: theory and applications to reliability and inference, data mining, bioinformatics, lifetime data, and neural networks
Skiadas, C.H.
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 economics and production, credit risk assessment, lifetime data analysis, risk models, supervised prediction with neural networks, and support models. The chapters emphasize new results with potential for solving real-world problems in various areas, including reliability and inference, data mining, multi-way data, analysis of textual data, bioinformatics, information theory, and statistical applications. Advances in Data Analysis is a useful reference for graduate students, researchers, and practitioners in statistics, mathematics, engineering, economics, social science, bioengineering, and bioscience. Real-world applications to economics, credit risk assessment, lifetime data analysis, risk models, neural networks, and support models 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, and bioscience INDICE: Preface.- Reliability and Inference.- Data Mining.- Quality Measures in Data Mining.- Multi-way Data.- Analysis of Textual Data.- Bioinformatics.- Stopping Times Analysis for Queues and Inventories.- Information Theory andStatistical Applications.- Statistical Applications in Economy and Production.- Modified Chi-squared and Non-parametric Goodness-of-fit Tests.- Credit RiskAssessment.- Lifetime Data analysis.- Asymptotic Behavior of Stochastic Processes and Random Fields.- Modelling Trends in Mortality Rates, Forecasting LifeExpectancy and Financial Implications.- Risk Models (Stochastic Models in Reliability).- Supervised Prediction with Neural Networks and Support Vector Machines (SVM).- Index.
- ISBN: 978-0-8176-4798-8
- Editorial: Birkhaüser
- Encuadernacion: Cartoné
- Páginas: 385
- Fecha Publicación: 01/10/2009
- Nº Volúmenes: 1
- Idioma: Inglés