Recent Advances In Stochastic Modeling And Data Analysis

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Recent Advances In Stochastic Modeling And Data Analysis

Author: Christos H Skiadas
language: en
Publisher: World Scientific
Release Date: 2007-11-16
This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics.
Recent Advances In Stochastic Operations Research

Operations research uses quantitative models to analyze and predict the behavior of systems and to provide information for decision makers. Two key concepts in operations research are optimization and uncertainty. This volume consists of a collection of peer reviewed papers from the International Workshop on Recent Advances in Stochastic Operations Research (RASOR 2005), August 25-26, 2005, Canmore, Alberta, Canada. In particular, the book focusses on models in stochastic operations research, including queueing models, inventory models, financial engineering models, reliability models, and simulations models.
Recent Advances in Stochastic Modeling and Data Analysis

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics. Sample Chapter(s). Chapter 1: An approach to Stochastic Process using Quasi-Arithmetic Means (373 KB). Contents: Stochastic Processes and Models; Distributions; Insurance; Stochastic Modeling for Healthcare Management; Markov and Semi Markov Models; Parametric/Non-Parametric; Dynamical Systems/Forecasting; Modeling and Stochastic Modeling; Statistical Applications in Socioeconimic Problems; Sampling and Optimization Problems; Data Mining and Applications; Clustering and Classification; Applications of Data Analysis; Miscellaneous. Readership: Researchers in probability and statistics, stochastics and fuzzy logic.