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| Author | : Roe Goodman |
| Publisher | : Courier Corporation |
| Total Pages | : 370 |
| Release | : 2006-01-01 |
| Genre | : Mathematics |
| ISBN | : 0486450376 |
Download Introduction to Stochastic Models Book in PDF, ePub and Kindle
Newly revised by the author, this undergraduate-level text introduces the mathematical theory of probability and stochastic processes. Using both computer simulations and mathematical models of random events, it comprises numerous applications to the physical and biological sciences, engineering, and computer science. Subjects include sample spaces, probabilities distributions and expectations of random variables, conditional expectations, Markov chains, and the Poisson process. Additional topics encompass continuous-time stochastic processes, birth and death processes, steady-state probabilities, general queuing systems, and renewal processes. Each section features worked examples, and exercises appear at the end of each chapter, with numerical solutions at the back of the book. Suggestions for further reading in stochastic processes, simulation, and various applications also appear at the end.
| Author | : Erhan Cinlar |
| Publisher | : Courier Corporation |
| Total Pages | : 418 |
| Release | : 2013-02-20 |
| Genre | : Mathematics |
| ISBN | : 0486276325 |
Download Introduction to Stochastic Processes Book in PDF, ePub and Kindle
Clear presentation employs methods that recognize computer-related aspects of theory. Topics include expectations and independence, Bernoulli processes and sums of independent random variables, Markov chains, renewal theory, more. 1975 edition.
| Author | : Barry L. Nelson |
| Publisher | : Courier Corporation |
| Total Pages | : 338 |
| Release | : 2012-10-11 |
| Genre | : Mathematics |
| ISBN | : 0486139948 |
Download Stochastic Modeling Book in PDF, ePub and Kindle
Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.
| Author | : Howard M. Taylor |
| Publisher | : Academic Press |
| Total Pages | : 410 |
| Release | : 2014-05-10 |
| Genre | : Mathematics |
| ISBN | : 1483269272 |
Download An Introduction to Stochastic Modeling Book in PDF, ePub and Kindle
An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.
| Author | : Gerard-Michel Cochard |
| Publisher | : John Wiley & Sons |
| Total Pages | : 310 |
| Release | : 2019-12-12 |
| Genre | : Computers |
| ISBN | : 1786304848 |
Download Introduction to Stochastic Processes and Simulation Book in PDF, ePub and Kindle
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.
| Author | : Petar Todorovic |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 302 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461397421 |
Download An Introduction to Stochastic Processes and Their Applications Book in PDF, ePub and Kindle
This text on stochastic processes and their applications is based on a set of lectures given during the past several years at the University of California, Santa Barbara (UCSB). It is an introductory graduate course designed for classroom purposes. Its objective is to provide graduate students of statistics with an overview of some basic methods and techniques in the theory of stochastic processes. The only prerequisites are some rudiments of measure and integration theory and an intermediate course in probability theory. There are more than 50 examples and applications and 243 problems and complements which appear at the end of each chapter. The book consists of 10 chapters. Basic concepts and definitions are pro vided in Chapter 1. This chapter also contains a number of motivating ex amples and applications illustrating the practical use of the concepts. The last five sections are devoted to topics such as separability, continuity, and measurability of random processes, which are discussed in some detail. The concept of a simple point process on R+ is introduced in Chapter 2. Using the coupling inequality and Le Cam's lemma, it is shown that if its counting function is stochastically continuous and has independent increments, the point process is Poisson. When the counting function is Markovian, the sequence of arrival times is also a Markov process. Some related topics such as independent thinning and marked point processes are also discussed. In the final section, an application of these results to flood modeling is presented.
| Author | : Vincenzo Capasso |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 348 |
| Release | : 2008-01-03 |
| Genre | : Mathematics |
| ISBN | : 0817644288 |
Download An Introduction to Continuous-Time Stochastic Processes Book in PDF, ePub and Kindle
This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. Balancing theory and applications, the authors use stochastic methods and concrete examples to model real-world problems from engineering, biomathematics, biotechnology, and finance. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. The book will be of interest to students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, physics, and engineering.
| Author | : Robert P. Dobrow |
| Publisher | : John Wiley & Sons |
| Total Pages | : 503 |
| Release | : 2016-03-07 |
| Genre | : Mathematics |
| ISBN | : 1118740653 |
Download Introduction to Stochastic Processes with R Book in PDF, ePub and Kindle
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 use of simulation, by means of the popular statistical software R, makes theoretical results come alive with practical, hands-on demonstrations. Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers’ problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features: More than 200 examples and 600 end-of-chapter exercises A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra Discussions of many timely and stimulating topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black–Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus Introductions to mathematics as needed in order to suit readers at many mathematical levels A companion web site that includes relevant data files as well as all R code and scripts used throughout the book Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.
| Author | : Olga Korosteleva |
| Publisher | : CRC Press |
| Total Pages | : 180 |
| Release | : 2022-02-14 |
| Genre | : Mathematics |
| ISBN | : 1000537374 |
Download Stochastic Processes with R Book in PDF, ePub and Kindle
Stochastic Processes with R: An Introduction cuts through the heavy theory that is present in most courses on random processes and serves as practical guide to simulated trajectories and real-life applications for stochastic processes. The light yet detailed text provides a solid foundation that is an ideal companion for undergraduate statistics students looking to familiarize themselves with stochastic processes before going on to more advanced courses. Key Features Provides complete R codes for all simulations and calculations Substantial scientific or popular applications of each process with occasional statistical analysis Helpful definitions and examples are provided for each process End of chapter exercises cover theoretical applications and practice calculations
| Author | : Don S. Lemons |
| Publisher | : Johns Hopkins University Press+ORM |
| Total Pages | : 165 |
| Release | : 2003-04-29 |
| Genre | : Science |
| ISBN | : 0801876389 |
Download An Introduction to Stochastic Processes in Physics Book in PDF, ePub and Kindle
This “lucid, masterfully written introduction to an often difficult subject . . . belongs on the bookshelf of every student of statistical physics” (Dr. Brian J. Albright, Applied Physics Division, Los Alamos National Laboratory). This book provides an accessible introduction to stochastic processes in physics and describes the basic mathematical tools of the trade: probability, random walks, and Wiener and Ornstein-Uhlenbeck processes. With an emphasis on applications, it includes end-of-chapter problems. Physicist and author Don S. Lemons builds on Paul Langevin’s seminal 1908 paper “On the Theory of Brownian Motion” and its explanations of classical uncertainty in natural phenomena. Following Langevin’s example, Lemons applies Newton’s second law to a “Brownian particle on which the total force included a random component.” This method builds on Newtonian dynamics and provides an accessible explanation to anyone approaching the subject for the first time. This volume contains the complete text of Paul Langevin’s “On the Theory of Brownian Motion,” translated by Anthony Gythiel.
