Statistical Topics And Stochastic Models For Dependent Data With Applications
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Statistical Topics and Stochastic Models for Dependent Data with Applications
Author: Vlad Stefan Barbu
language: en
Publisher: John Wiley & Sons
Release Date: 2020-11-03
This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.
Proceedings of the International Workshop on Navigating the Digital Business Frontier for Sustainable Financial Innovation (ICDEBA 2024)
This is an open access book. Against this background, the International Conference on Digital Economy and Business Administration in 2024 will establish three sub-venues, aiming to further deepen academic research and practical discussions in this field. This sub-venue will delve into the development of digital economy and finance, highlight practical experiences in digital financial ecosystem construction, and explore the comprehensive impact of digital economy on the financial industry. Additionally, the sub-venue will invite local innovative financial enterprises to share their practical achievements, showcasing advanced applications of digital technology in financial services. This sub-venue looks forward to deepening the profound understanding of the development of digital economy and finance in this conference, promoting scholars, researchers, and industry professionals to achieve deeper cooperation and innovation in this field. This will not only contribute to the sustainable development of Hangzhou's digital economy and finance but also provide valuable experience and references for research and practices in the global digital economy and finance field, promoting the sustainable development of the industry.
Stochastic Modeling and Optimization Methods for Critical Infrastructure Protection, Volume 2
Author: Alexei A. Gaivoronski
language: en
Publisher: John Wiley & Sons
Release Date: 2025-05-13
Stochastic Modeling and Optimization Methods for Critical Infrastructure Protection is a thorough exploration of mathematical models and tools that are designed to strengthen critical infrastructures against threats – both natural and adversarial. Divided into two volumes, this first volume examines stochastic modeling across key economic sectors and their interconnections, while the second volume focuses on advanced mathematical methods for enhancing infrastructure protection. The book covers a range of themes, including risk assessment techniques that account for systemic interdependencies within modern technospheres, the dynamics of uncertainty, instability and system vulnerabilities. The book also presents other topics such as cryptographic information protection and Shannon’s theory of secret systems, alongside solutions arising from optimization, game theory and machine learning approaches. Featuring research from international collaborations, this book covers both theory and applications, offering vital insights for advanced risk management curricula. It is intended not only for researchers, but also educators and professionals in infrastructure protection and stochastic optimization.