Stochastic Modeling And Statistical Methods
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Stochastic Modeling and Statistical Methods
Author: Ioannis S. Triantafyllou
language: en
Publisher: Academic Press
Release Date: 2025-06-01
Stochastic Modeling and Statistical Methods: Advances and Applications is the practical guide to the latest developments in data analysis and research methods. The book explores the significant research progress that has been seen in recent decades, offering vital tools for analyzing modern applications and real data. Topics covered include Dynamic Reliability, Stochastic Modeling, System Maintainability, and Parametric, Semi-Parametric, and Nonparametric Statistical Inference. Readers will find the latest advancements in these areas, making it an essential resource for researchers and practitioners who want to explore these evolving fields and stay updated on cutting-edge research. - Presents the latest breakthroughs in Reliability Engineering, along with current perspectives on the field - Includes shared, practical knowledge of contemporary statistical modeling techniques, thus enhancing analytical skills - Covers the probabilistic methods used to investigate various applications in Reliability Engineering
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.
Stochastic Modeling and Mathematical Statistics
Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well