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Introduction To The Theory Of Stochastic Processes Depending On A Continuous Parameter
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Book Synopsis Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter by : Henry Berthold Mann
Download or read book Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter written by Henry Berthold Mann and published by . This book was released on 1953 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to the theory of stochastic processes depending on a continuous parameter by : Henry B. Mann
Download or read book Introduction to the theory of stochastic processes depending on a continuous parameter written by Henry B. Mann and published by . This book was released on 1953 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter by : Henry B. Mann
Download or read book Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter written by Henry B. Mann and published by . This book was released on 1951 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter. Henry B. Mann. [Foreword by J. H. Curtiss.]. by : Henry B. Mann
Download or read book Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter. Henry B. Mann. [Foreword by J. H. Curtiss.]. written by Henry B. Mann and published by . This book was released on 1953 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter by : Henry Berthold Mann
Download or read book Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter written by Henry Berthold Mann and published by . This book was released on 1953 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter by : États-Unis. National bureau of standards
Download or read book Introduction to the Theory of Stochastic Processes Depending on a Continuous Parameter written by États-Unis. National bureau of standards and published by . This book was released on 1952 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Theory of Stochastic Processes Depending on Continuous Parameter by :
Download or read book Introduction to Theory of Stochastic Processes Depending on Continuous Parameter written by and published by . This book was released on 1953 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Introduction to Continuous-Time Stochastic Processes by : Vincenzo Capasso
Download or read book An Introduction to Continuous-Time Stochastic Processes written by Vincenzo Capasso and published by Birkhäuser. This book was released on 2015-05-29 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook, now in its third 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, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Key topics include: Markov processes Stochastic differential equations Arbitrage-free markets and financial derivatives Insurance risk Population dynamics, and epidemics Agent-based models New to the Third Edition: Infinitely divisible distributions Random measures Levy processes Fractional Brownian motion Ergodic theory Karhunen-Loeve expansion Additional applications Additional exercises Smoluchowski approximation of Langevin systems An Introduction to Continuous-Time Stochastic Processes, Third Edition will be of interest to a broad audience of students, pure and applied mathematicians, and researchers and practitioners in mathematical finance, biomathematics, biotechnology, and engineering. Suitable as a textbook for graduate or undergraduate courses, as well as European Masters courses (according to the two-year-long second cycle of the “Bologna Scheme”), the work may also be used for self-study or as a reference. 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. From reviews of previous editions: "The book is ... an account of fundamental concepts as they appear in relevant modern applications and literature. ... The book addresses three main groups: first, mathematicians working in a different field; second, other scientists and professionals from a business or academic background; third, graduate or advanced undergraduate students of a quantitative subject related to stochastic theory and/or applications." -Zentralblatt MATH
Book Synopsis Introduction to Stochastic Processes Using R by : Sivaprasad Madhira
Download or read book Introduction to Stochastic Processes Using R written by Sivaprasad Madhira and published by Springer Nature. This book was released on 2023-12-05 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents some basic stochastic processes, mainly Markov processes. It begins with a brief introduction to the framework of stochastic processes followed by the thorough discussion on Markov chains, which is the simplest and the most important class of stochastic processes. The book then elaborates the theory of Markov chains in detail including classification of states, the first passage distribution, the concept of periodicity and the limiting behaviour of a Markov chain in terms of associated stationary and long run distributions. The book first illustrates the theory for some typical Markov chains, such as random walk, gambler's ruin problem, Ehrenfest model and Bienayme-Galton-Watson branching process; and then extends the discussion when time parameter is continuous. It presents some important examples of a continuous time Markov chain, which include Poisson process, birth process, death process, birth and death processes and their variations. These processes play a fundamental role in the theory and applications in queuing and inventory models, population growth, epidemiology and engineering systems. The book studies in detail the Poisson process, which is the most frequently applied stochastic process in a variety of fields, with its extension to a renewal process. The book also presents important basic concepts on Brownian motion process, a stochastic process of historic importance. It covers its few extensions and variations, such as Brownian bridge, geometric Brownian motion process, which have applications in finance, stock markets, inventory etc. The book is designed primarily to serve as a textbook for a one semester introductory course in stochastic processes, in a post-graduate program, such as Statistics, Mathematics, Data Science and Finance. It can also be used for relevant courses in other disciplines. Additionally, it provides sufficient background material for studying inference in stochastic processes. The book thus fulfils the need of a concise but clear and student-friendly introduction to various types of stochastic processes.
Book Synopsis Introduction to Stochastic Processes by : Erhan Cinlar
Download or read book Introduction to Stochastic Processes written by Erhan Cinlar and published by Courier Corporation. This book was released on 2013-02-20 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Stochastic Processes by : J. L. Doob
Download or read book Stochastic Processes written by J. L. Doob and published by Wiley-Interscience. This book was released on 1990-01-25 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory of stochastic processes has developed so much in the last twenty years that the need for a systematic account of the subject has been felt, particularly by students and instructors of probability. This book fills that need. While even elementary definitions and theorems are stated in detail, this is not recommended as a first text in probability and there has been no compromise with the mathematics of probability. Since readers complained that omission of certain mathematical detail increased the obscurity of the subject, the text contains various mathematical points that might otherwise seem extraneous. A supplement includes a treatment of the various aspects of measure theory. A chapter on the specialized problem of prediction theory has also been included and references to the literature and historical remarks have been collected in the Appendix.
Book Synopsis Introduction to Stochastic Processes with R by : Robert P. Dobrow
Download or read book Introduction to Stochastic Processes with R written by Robert P. Dobrow and published by John Wiley & Sons. This book was released on 2016-03-07 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Stochastic Processes by : Andrei N Borodin
Download or read book Stochastic Processes written by Andrei N Borodin and published by Birkhäuser. This book was released on 2017-10-30 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.
Book Synopsis An Introduction to Stochastic Modeling by : Howard M. Taylor
Download or read book An Introduction to Stochastic Modeling written by Howard M. Taylor and published by Academic Press. This book was released on 2014-05-10 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Topics in Stochastic Processes by : Robert B. Ash
Download or read book Topics in Stochastic Processes written by Robert B. Ash and published by . This book was released on 1975 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Processes, Introduction, Covariance functions, Second order calculus, Karhunen-loeve expansion, Estimation problems, Notes; Spectral theory and prediction, Introduction, L Stochastic integrals, Decomposition of stationary processes, Examples of discrete parameter processes, Discrete parameter prediction: Special cases, Discrete parameter prediction: General solution, Examples of continuous parameter processes; Continuos parameter prediction special cases; yaglom's method, Some stochastic differential equations, Continuos parameter prediction: remarks on the general solution, Notes; Ergodic theory, Ergodicity and mixing, The pointwise ergodic theorem, Applications to real analysis, Applications to Markov chains, The Shannon-mcMillan theorem, Notes; Sample function analysis of continuous parameter stochastic processes, Separability, Measurability, One-Dimensional brownian motion, Law of the iterated logarithm, Markov processes, Processes with independent increments, Continuous parameter martingales, The strong Markov property, Notes; The ito integral and stochastic differential equations, Definitions of the ito integral, Existence and uniqueness theorems for stochastic differential equations, Stochastic differentials: A chain rule, Notes.
Book Synopsis Introduction to Random Processes by : Yurii A. Rozanov
Download or read book Introduction to Random Processes written by Yurii A. Rozanov and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, the theory of random processes represents a large field of mathematics with many different branches, and the task of choosing topics for a brief introduction to this theory is far from being simple. This introduction to the theory of random processes uses mathematical models that are simple, but have some importance for applications. We consider different processes, whose development in time depends on some random factors. The fundamental problem can be briefly circumscribed in the following way: given some relatively simple characteristics of a process, compute the probability of another event which may be very complicated; or estimate a random variable which is related to the behaviour of the process. The models that we consider are chosen in such a way that it is possible to discuss the different methods of the theory of random processes by referring to these models. The book starts with a treatment of homogeneous Markov processes with a countable number of states. The main topic is the ergodic theorem, the method of Kolmogorov's differential equations (Secs. 1-4) and the Brownian motion process, the connecting link being the transition from Kolmogorov's differential-difference equations for random walk to a limit diffusion equation (Sec. 5).
Book Synopsis An Introduction to Stochastic Processes by : M. S. Bartlett
Download or read book An Introduction to Stochastic Processes written by M. S. Bartlett and published by CUP Archive. This book was released on 1978 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random sequences; Processes in continuous time; Miscellaneous statistical applications; Limiting stochastic operations; Stationary processes; Prediction and communication theory; The statistical analysis of stochastic processes; Correlation analysis of time-series.
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