Advances in Data Analysis: Theory and 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.