Introduction Aux Processus Stochastiques Et La Simulation
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Introduction Aux Processus Stochastiques Et La Simulation
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Author : Gérard-Michel Cochard
language : fr
Publisher: ISTE Group
Release Date : 2019-01-01
Introduction Aux Processus Stochastiques Et La Simulation written by Gérard-Michel Cochard and has been published by ISTE Group this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-01 with Simulation methods categories.
Maîtriser le hasard a longtemps été une préoccupation de recherche des mathématiciens. Aujourd'hui, nous possédons une approche prédictive de l'évolution des systèmes basée sur la théorie des probabilités. Cependant, découvrir ce sujet est parfois complexe, car il nécessite une bonne connaissance des mathématiques sous-jacentes. Cet ouvrage offre une introduction aux processus liés aux fluctuations du hasard et à l'emploi de méthodes numériques pour approcher des solutions difficiles à obtenir par une voie analytique. Il reprend des exemples classiques de gestion de stocks et de files d'attente, et aborde des sujets plus divers, comme la fiabilité des équipements, la génétique, la dynamique des populations, la physique et même la finance de marchés. Il s’adresse à des étudiants de niveau Master, d’école d’ingénieur ou de gestion, mais aussi à un public de formation continue, afin de faire découvrir le vaste domaine de l’aide à la décision.
Introduction To Stochastic Processes And Simulation
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Author : Gerard-Michel Cochard
language : en
Publisher: John Wiley & Sons
Release Date : 2019-12-12
Introduction To Stochastic Processes And Simulation written by Gerard-Michel Cochard and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-12 with Computers categories.
Mastering chance has, for a long time, been a preoccupation of mathematical research. Today, we possess a predictive approach to the evolution of systems based on the theory of probabilities. Even so, uncovering this subject is sometimes complex, because it necessitates a good knowledge of the underlying mathematics. This book offers an introduction to the processes linked to the fluctuations in chance and the use of numerical methods to approach solutions that are difficult to obtain through an analytical approach. It takes classic examples of inventory and queueing management, and addresses more diverse subjects such as equipment reliability, genetics, population dynamics, physics and even market finance. It is addressed to those at Masters level, at university, engineering school or management school, but also to an audience of those in continuing education, in order that they may discover the vast field of decision support.
Introduction To Scientific Programming And Simulation Using R
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Author : Owen Jones
language : en
Publisher: CRC Press
Release Date : 2014-06-12
Introduction To Scientific Programming And Simulation Using R written by Owen Jones and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-12 with Mathematics categories.
Learn How to Program Stochastic ModelsHighly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear,
Introduction To Scientific Programming And Simulation Using R Second Edition
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Author : Owen Jones
language : en
Publisher: CRC Press
Release Date : 2014-06-12
Introduction To Scientific Programming And Simulation Using R Second Edition written by Owen Jones and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-12 with Mathematics categories.
Learn How to Program Stochastic Models Highly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data. The book’s four parts teach: Core knowledge of R and programming concepts How to think about mathematics from a numerical point of view, including the application of these concepts to root finding, numerical integration, and optimisation Essentials of probability, random variables, and expectation required to understand simulation Stochastic modelling and simulation, including random number generation and Monte Carlo integration In a new chapter on systems of ordinary differential equations (ODEs), the authors cover the Euler, midpoint, and fourth-order Runge-Kutta (RK4) schemes for solving systems of first-order ODEs. They compare the numerical efficiency of the different schemes experimentally and show how to improve the RK4 scheme by using an adaptive step size. Another new chapter focuses on both discrete- and continuous-time Markov chains. It describes transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It also presents methods for simulating discrete- and continuous-time chains as well as techniques for defining the state space, including lumping states and supplementary variables. Building readers’ statistical intuition, Introduction to Scientific Programming and Simulation Using R, Second Edition shows how to turn algorithms into code. It is designed for those who want to make tools, not just use them. The code and data are available for download from CRAN.
Stochastic Simulation And Monte Carlo Methods
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Author : Carl Graham
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-07-16
Stochastic Simulation And Monte Carlo Methods written by Carl Graham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-16 with Mathematics categories.
In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.
An Introduction To The Numerical Simulation Of Stochastic Di Erential Equations
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Author : Desmond J. Higham
language : en
Publisher: SIAM
Release Date : 2021-01-28
An Introduction To The Numerical Simulation Of Stochastic Di Erential Equations written by Desmond J. Higham and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-28 with Mathematics categories.
This book provides a lively and accessible introduction to the numerical solution of stochastic differential equations with the aim of making this subject available to the widest possible readership. It presents an outline of the underlying convergence and stability theory while avoiding technical details. Key ideas are illustrated with numerous computational examples and computer code is listed at the end of each chapter. The authors include 150 exercises, with solutions available online, and 40 programming tasks. Although introductory, the book covers a range of modern research topics, including Itô versus Stratonovich calculus, implicit methods, stability theory, nonconvergence on nonlinear problems, multilevel Monte Carlo, approximation of double stochastic integrals, and tau leaping for chemical and biochemical reaction networks. An Introduction to the Numerical Simulation of Stochastic Differential Equations is appropriate for undergraduates and postgraduates in mathematics, engineering, physics, chemistry, finance, and related disciplines, as well as researchers in these areas. The material assumes only a competence in algebra and calculus at the level reached by a typical first-year undergraduate mathematics class, and prerequisites are kept to a minimum. Some familiarity with basic concepts from numerical analysis and probability is also desirable but not necessary.
An Introduction To The Regenerative Method For Simulation Analysis
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Author : M. A. Crane
language : en
Publisher: Springer
Release Date : 1977
An Introduction To The Regenerative Method For Simulation Analysis written by M. A. Crane and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with Computers categories.
The purpose of this report is to provide an introduction to the regenerative method for simulation analysis. The simulations are simulations of stochastic systems, i.e., systems with random elements. The regenerative approach leads to a statistical methodology for analyzing the output of those simulations which have the property of 'starting afresh probabilistically' from time to time. The class of such simulations is very large and very important, including simulations of a broad variety of queues and queueing networks, inventory systems, inspection, maintenance, and repair operations, and numerous other situations.
An Introduction To Continuous Time Stochastic Processes
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Author : Vincenzo Capasso
language : en
Publisher: Springer Nature
Release Date : 2021-06-18
An Introduction To Continuous Time Stochastic Processes written by Vincenzo Capasso and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-18 with Mathematics categories.
This textbook, now in its fourth edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations. Expertly balancing theory and applications, it features concrete examples of modeling real-world problems from biology, medicine, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Unlike other books on stochastic methods that specialize in a specific field of applications, this volume examines the ways in which similar stochastic methods can be applied across different fields. Beginning with the fundamentals of probability, the authors go on to introduce the theory of stochastic processes, the Itô Integral, and stochastic differential equations. The following chapters then explore stability, stationarity, and ergodicity. The second half of the book is dedicated to applications to a variety of fields, including finance, biology, and medicine. Some highlights of this fourth edition include a more rigorous introduction to Gaussian white noise, additional material on the stability of stochastic semigroups used in models of population dynamics and epidemic systems, and the expansion of methods of analysis of one-dimensional stochastic differential equations. An Introduction to Continuous-Time Stochastic Processes, Fourth Edition is intended for graduate students taking an introductory course on stochastic processes, applied probability, stochastic calculus, mathematical finance, or mathematical biology. Prerequisites include knowledge of calculus and some analysis; exposure to probability would be helpful but not required since the necessary fundamentals of measure and integration are provided. Researchers and practitioners in mathematical finance, biomathematics, biotechnology, and engineering will also find this volume to be of interest, particularly the applications explored in the second half of the book.
Introduction To Rare Event Simulation
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Author : James Bucklew
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Introduction To Rare Event Simulation written by James Bucklew and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
This book presents a unified theory of rare event simulation and the variance reduction technique known as importance sampling from the point of view of the probabilistic theory of large deviations. It allows us to view a vast assortment of simulation problems from a unified single perspective.
Introduction To Stochastic Search And Optimization
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Author : James C. Spall
language : en
Publisher: John Wiley & Sons
Release Date : 2005-03-11
Introduction To Stochastic Search And Optimization written by James C. Spall and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-03-11 with Mathematics categories.
* Unique in its survey of the range of topics. * Contains a strong, interdisciplinary format that will appeal to both students and researchers. * Features exercises and web links to software and data sets.