R. Cairoli Sequential Stochastic Optimization
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Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a
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Robert P. Dobrow Introduction to Stochastic Processes with R
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An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The
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Группа авторов Stochastic Simulation
Купить за 14174.93 RUR
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of
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Reuven Y. Rubinstein Fast Sequential Monte Carlo Methods for Counting and Optimization
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A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization
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Jacques Janssen Basic Stochastic Processes
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This book presents basic stochastic processes, stochastic calculus including L?vy processes on one hand, and Markov and Semi Markov models on the other. From the financial point of view, essential concepts such as the Black and Scholes model, VaR indicators, actuarial evaluation, market values,
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Spark Lamborghini SC63 Lamborghini Железные Звенья 2024 24 часа Ле-Мана Cairoli 1/43 #19 R. Грожан/А. Калдарелли/М. (Готовая модель)
Купить за 11990 RUR
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Ra?l Toral Stochastic Numerical Methods
Купить за 8075.95 RUR
Stochastic Numerical Methods introduces at Master level the numerical methods that use probability or stochastic concepts to analyze random processes. The book aims at being rather general and is addressed at students of natural sciences (Physics, Chemistry, Mathematics, Biology, etc.) and
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Ionut Florescu Probability and Stochastic Processes
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A comprehensive and accessible presentation of probability and stochastic processes with emphasis on key theoretical concepts and real-world applications With a sophisticated approach, Probability and Stochastic Processes successfully balances theory and applications in a pedagogical and accessible
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Michael J. Panik Stochastic Differential Equations
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A beginner’s guide to stochastic growth modeling The chief advantage of stochastic growth models over deterministic models is that they combine both deterministic and stochastic elements of dynamic behaviors, such as weather, natural disasters, market fluctuations, and epidemics. This makes
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Nikolaos Limnios Introduction to Stochastic Models
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This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences. It covers Markov and semi-Markov models, as well as their particular cases:
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Reinhard Mahnke Physics of Stochastic Processes
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Based on lectures given by one of the authors with many years of experience in teaching stochastic processes, this textbook is unique in combining basic mathematical and physical theory with numerous simple and sophisticated examples as well as detailed calculations. In addition, applications from
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Jie Li Stochastic Dynamics of Structures
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In Stochastic Dynamics of Structures, Li and Chen present a unified view of the theory and techniques for stochastic dynamics analysis, prediction of reliability, and system control of structures within the innovative theoretical framework of physical stochastic systems. The authors outline the
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