Advances in Algorithmic Methods for Stochastic Models PDF Download
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Author:
Publisher:
ISBN:
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Languages : en
Pages : 433
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 433
Get Book Here
Book Description
Author: Guy Latouche
Publisher: Notable Publications, Incorporated
ISBN: 9780966584714
Category : Markov processes
Languages : en
Pages : 433
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Book Description
Author: Quan-Lin Li
Publisher: Springer Science & Business Media
ISBN: 364211492X
Category : Mathematics
Languages : en
Pages : 693
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Book Description
"Constructive Computation in Stochastic Models with Applications: The RG-Factorizations" provides a unified, constructive and algorithmic framework for numerical computation of many practical stochastic systems. It summarizes recent important advances in computational study of stochastic models from several crucial directions, such as stationary computation, transient solution, asymptotic analysis, reward processes, decision processes, sensitivity analysis as well as game theory. Graduate students, researchers and practicing engineers in the field of operations research, management sciences, applied probability, computer networks, manufacturing systems, transportation systems, insurance and finance, risk management and biological sciences will find this book valuable. Dr. Quan-Lin Li is an Associate Professor at the Department of Industrial Engineering of Tsinghua University, China.
Author: Christos H Skiadas
Publisher: World Scientific
ISBN: 9814474479
Category : Mathematics
Languages : en
Pages : 669
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Book Description
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.
Author: Albert N. Shiryaev
Publisher: Springer Nature
ISBN: 303083266X
Category : Mathematics
Languages : en
Pages : 370
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Book Description
Highlighting the latest advances in stochastic analysis and its applications, this volume collects carefully selected and peer-reviewed papers from the 5th International Conference on Stochastic Methods (ICSM-5), held in Moscow, Russia, November 23-27, 2020. The contributions deal with diverse topics such as stochastic analysis, stochastic methods in computer science, analytical modeling, asymptotic methods and limit theorems, Markov processes, martingales, insurance and financial mathematics, queueing theory and stochastic networks, reliability theory, risk analysis, statistical methods and applications, machine learning and data analysis. The 29 articles in this volume are a representative sample of the 87 high-quality papers accepted and presented during the conference. The aim of the ICSM-5 conference is to promote the collaboration of researchers from Russia and all over the world, and to contribute to the development of the field of stochastic analysis and applications of stochastic models.
Author: Ansgar Steland
Publisher: Springer Nature
ISBN: 3030286657
Category : Mathematics
Languages : en
Pages : 450
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Book Description
This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.
Author: Jacques Janssen
Publisher: Springer Science & Business Media
ISBN: 9401706638
Category : Mathematics
Languages : en
Pages : 428
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Book Description
Advances in Stochastic Modelling and Data Analysis presents the most recent developments in the field, together with their applications, mainly in the areas of insurance, finance, forecasting and marketing. In addition, the possible interactions between data analysis, artificial intelligence, decision support systems and multicriteria analysis are examined by top researchers. Audience: A wide readership drawn from theoretical and applied mathematicians, such as operations researchers, management scientists, statisticians, computer scientists, bankers, marketing managers, forecasters, and scientific societies such as EURO and TIMS.
Author: Marie Duflo
Publisher: Springer Science & Business Media
ISBN: 3662128802
Category : Mathematics
Languages : en
Pages : 394
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Book Description
An up-to-date, self-contained review of a wide range of recursive methods for stabilization, identification and control of complex stochastic models (guiding a rocket or a plane, organizing multi-access broadcast channels, self-learning of neural networks ...). Suitable for mathematicians (researchers and also students) and engineers.
Author: Waltraud Kahle
Publisher: Springer Science & Business Media
ISBN: 9780817640491
Category : Mathematics
Languages : en
Pages : 426
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Book Description
In 24 papers from a 1997 workshop near Magdeburg, Germany, theoreticians, applied statisticians, and practitioners discuss their current work and compare and evaluate models and methods. Within sections on lifetime analysis, reliability analysis, network analysis, and process control, they consider such topics as acceptance regions and their application in lifetime estimation, stochastic models for the return of used devices, a unified approach to the reliability of recurrent structures, and controlling a process with three different states. Annotation copyrighted by Book News, Inc., Portland, OR
Author: Guy Latouche
Publisher: Springer Science & Business Media
ISBN: 146144909X
Category : Mathematics
Languages : en
Pages : 265
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Book Description
Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models. Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., performance measures) of the underlying stochastic processes, and apply these probabilistic structures and/or computational algorithms within a wide variety of fields. This volume presents recent research results on: the theory, algorithms and methodologies concerning matrix-analytic and related methods in stochastic models; and the application of matrix-analytic and related methods in various fields, which includes but is not limited to computer science and engineering, communication networks and telephony, electrical and industrial engineering, operations research, management science, financial and risk analysis, and bio-statistics. These research studies provide deep insights and understanding of the stochastic models of interest from a mathematics and/or applications perspective, as well as identify directions for future research.
