Advances in Data Analysis: Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks
by Christos H. Skiadas 2021-01-03 07:32:27
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An outgrowth of the 12thInternational 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 inferenc... Read more

An outgrowth of the 12thInternational 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 Analysisis a useful reference for graduate students, researchers, and practitioners in statistics, mathematics, engineering, economics, social science, bioengineering, and bioscience.

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  • ISBN
  • 9780817647988
Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete. He is chair of the Demographics Workshop series, the Applie...
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