Probability And Stochastic Modeling

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Stochastic Modeling

Author : Nicolas Lanchier
Publisher : Springer
ISBN 13 : 3319500384
Total Pages : 303 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Stochastic Modeling by : Nicolas Lanchier

Download or read book Stochastic Modeling written by Nicolas Lanchier and published by Springer. This book was released on 2017-01-27 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the gambler’s ruin chain, branching processes, symmetric random walks, and queueing systems. The third, more research-oriented part of the text, discusses special stochastic processes of interest in physics, biology, and sociology. Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright –Fisher model, Kingman’s coalescent, percolation models, the contact process, and the voter model. Further treatment of the material explains how these special processes are connected to each other from a modeling perspective as well as their simulation capabilities in C and MatlabTM.

Probability and Stochastic Modeling

Author : Vladimir I. Rotar
Publisher : CRC Press
ISBN 13 : 1439872066
Total Pages : 510 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Probability and Stochastic Modeling by : Vladimir I. Rotar

Download or read book Probability and Stochastic Modeling written by Vladimir I. Rotar and published by CRC Press. This book was released on 2012-08-25 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: A First Course in Probability with an Emphasis on Stochastic Modeling Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different approaches and help students grasp general concepts and theoretical results. The text is suitable for majors in mathematics and statistics as well as majors in computer science, economics, finance, and physics. The author offers two explicit options to teaching the material, which is reflected in "routes" designated by special "roadside" markers. The first route contains basic, self-contained material for a one-semester course. The second provides a more complete exposition for a two-semester course or self-study.

Concepts in Probability and Stochastic Modeling

Author : James J. Higgins
Publisher : Duxbury Resource Center
ISBN 13 :
Total Pages : 440 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Concepts in Probability and Stochastic Modeling by : James J. Higgins

Download or read book Concepts in Probability and Stochastic Modeling written by James J. Higgins and published by Duxbury Resource Center. This book was released on 1995 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text stresses modern ideas, including simulation and interpretation of results. It focuses on the aspects of probability most relevant to applications, such as stochastic modeling, Markov chains, reliability, and queuing.

An Introduction to Stochastic Modeling

Author : Howard M. Taylor
Publisher : Academic Press
ISBN 13 : 1483269272
Total Pages : 410 pages
Book Rating : 4.4/5 (832 download)

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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.

Introduction to Stochastic Models

Author : Roe Goodman
Publisher : Courier Corporation
ISBN 13 : 0486450376
Total Pages : 370 pages
Book Rating : 4.4/5 (864 download)

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Book Synopsis Introduction to Stochastic Models by : Roe Goodman

Download or read book Introduction to Stochastic Models written by Roe Goodman and published by Courier Corporation. This book was released on 2006-01-01 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Stochastic Simulation and Monte Carlo Methods

Author : Carl Graham
Publisher : Springer Science & Business Media
ISBN 13 : 3642393632
Total Pages : 260 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Stochastic Simulation and Monte Carlo Methods by : Carl Graham

Download or read book Stochastic Simulation and Monte Carlo Methods written by Carl Graham and published by Springer Science & Business Media. This book was released on 2013-07-16 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Foundations of Stochastic Analysis

Author : M. M. Rao
Publisher : Courier Corporation
ISBN 13 : 0486296539
Total Pages : 320 pages
Book Rating : 4.4/5 (862 download)

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Book Synopsis Foundations of Stochastic Analysis by : M. M. Rao

Download or read book Foundations of Stochastic Analysis written by M. M. Rao and published by Courier Corporation. This book was released on 2013-04-17 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume considers fundamental theories and contrasts the natural interplay between real and abstract methods. No prior knowledge of probability is assumed. Numerous problems, most with hints. 1981 edition.

Stochastic Modeling of Scientific Data

Author : Peter Guttorp
Publisher : CRC Press
ISBN 13 : 135141366X
Total Pages : 384 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Stochastic Modeling of Scientific Data by : Peter Guttorp

Download or read book Stochastic Modeling of Scientific Data written by Peter Guttorp and published by CRC Press. This book was released on 2018-03-29 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics.

The Data Science Handbook

Author : Field Cady
Publisher : John Wiley & Sons
ISBN 13 : 1119092949
Total Pages : 420 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis The Data Science Handbook by : Field Cady

Download or read book The Data Science Handbook written by Field Cady and published by John Wiley & Sons. This book was released on 2017-02-28 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

Stochastic Modelling of Social Processes

Author : Andreas Diekmann
Publisher : Academic Press
ISBN 13 : 1483266567
Total Pages : 352 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Stochastic Modelling of Social Processes by : Andreas Diekmann

Download or read book Stochastic Modelling of Social Processes written by Andreas Diekmann and published by Academic Press. This book was released on 2014-05-10 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction. Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of job and career mobility, which is one of the approaches taken by sociologists in research on the labor market. Other chapters consider the characteristic trends and patterns from data on divorces. This book discusses as well the two approaches of stochastic modeling of social processes, namely competing risk models and semi-Markov processes. The final chapter deals with the practical application of regression models of survival data. This book is a valuable resource for social scientists and statisticians.

Monte Carlo Methods in Financial Engineering

Author : Paul Glasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387216170
Total Pages : 603 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Monte Carlo Methods in Financial Engineering by : Paul Glasserman

Download or read book Monte Carlo Methods in Financial Engineering written by Paul Glasserman and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis

Stochastic Modeling

Author : Barry L. Nelson
Publisher : Courier Corporation
ISBN 13 : 0486139948
Total Pages : 338 pages
Book Rating : 4.4/5 (861 download)

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Book Synopsis Stochastic Modeling by : Barry L. Nelson

Download or read book Stochastic Modeling written by Barry L. Nelson and published by Courier Corporation. This book was released on 2012-10-11 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Probability, Stochastic Processes, and Queueing Theory

Author : Randolph Nelson
Publisher : Springer Science & Business Media
ISBN 13 : 1475724268
Total Pages : 595 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Probability, Stochastic Processes, and Queueing Theory by : Randolph Nelson

Download or read book Probability, Stochastic Processes, and Queueing Theory written by Randolph Nelson and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: We will occasionally footnote a portion of text with a "**,, to indicate Notes on the that this portion can be initially bypassed. The reasons for bypassing a Text portion of the text include: the subject is a special topic that will not be referenced later, the material can be skipped on first reading, or the level of mathematics is higher than the rest of the text. In cases where a topic is self-contained, we opt to collect the material into an appendix that can be read by students at their leisure. The material in the text cannot be fully assimilated until one makes it Notes on "their own" by applying the material to specific problems. Self-discovery Problems is the best teacher and although they are no substitute for an inquiring mind, problems that explore the subject from different viewpoints can often help the student to think about the material in a uniquely per sonal way. With this in mind, we have made problems an integral part of this work and have attempted to make them interesting as well as informative.

Stochastic Modeling and Mathematical Statistics

Author : Francisco J. Samaniego
Publisher : CRC Press
ISBN 13 : 1466560479
Total Pages : 622 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Stochastic Modeling and Mathematical Statistics by : Francisco J. Samaniego

Download or read book Stochastic Modeling and Mathematical Statistics written by Francisco J. Samaniego and published by CRC Press. This book was released on 2014-01-14 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well

Introduction to Probability Models

Author : Sheldon M. Ross
Publisher : Academic Press
ISBN 13 : 0123756871
Total Pages : 801 pages
Book Rating : 4.1/5 (237 download)

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Book Synopsis Introduction to Probability Models by : Sheldon M. Ross

Download or read book Introduction to Probability Models written by Sheldon M. Ross and published by Academic Press. This book was released on 2006-12-11 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Probability Models, Tenth Edition, provides an introduction to elementary probability theory and stochastic processes. There are two approaches to the study of probability theory. One is heuristic and nonrigorous, and attempts to develop in students an intuitive feel for the subject that enables him or her to think probabilistically. The other approach attempts a rigorous development of probability by using the tools of measure theory. The first approach is employed in this text. The book begins by introducing basic concepts of probability theory, such as the random variable, conditional probability, and conditional expectation. This is followed by discussions of stochastic processes, including Markov chains and Poison processes. The remaining chapters cover queuing, reliability theory, Brownian motion, and simulation. Many examples are worked out throughout the text, along with exercises to be solved by students. This book will be particularly useful to those interested in learning how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. Ideally, this text would be used in a one-year course in probability models, or a one-semester course in introductory probability theory or a course in elementary stochastic processes. New to this Edition: 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, and test bank Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field Hallmark features: Superior writing style Excellent exercises and examples covering the wide breadth of coverage of probability topics Real-world applications in engineering, science, business and economics

Introduction to Probability and Stochastic Processes with Applications

Author : Liliana Blanco Castañeda
Publisher : John Wiley & Sons
ISBN 13 : 1118344960
Total Pages : 741 pages
Book Rating : 4.1/5 (183 download)

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Book Synopsis Introduction to Probability and Stochastic Processes with Applications by : Liliana Blanco Castañeda

Download or read book Introduction to Probability and Stochastic Processes with Applications written by Liliana Blanco Castañeda and published by John Wiley & Sons. This book was released on 2014-08-21 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: An easily accessible, real-world approach to probability and stochastic processes Introduction to Probability and Stochastic Processes with Applications presents a clear, easy-to-understand treatment of probability and stochastic processes, providing readers with a solid foundation they can build upon throughout their careers. With an emphasis on applications in engineering, applied sciences, business and finance, statistics, mathematics, and operations research, the book features numerous real-world examples that illustrate how random phenomena occur in nature and how to use probabilistic techniques to accurately model these phenomena. The authors discuss a broad range of topics, from the basic concepts of probability to advanced topics for further study, including Itô integrals, martingales, and sigma algebras. Additional topical coverage includes: Distributions of discrete and continuous random variables frequently used in applications Random vectors, conditional probability, expectation, and multivariate normal distributions The laws of large numbers, limit theorems, and convergence of sequences of random variables Stochastic processes and related applications, particularly in queueing systems Financial mathematics, including pricing methods such as risk-neutral valuation and the Black-Scholes formula Extensive appendices containing a review of the requisite mathematics and tables of standard distributions for use in applications are provided, and plentiful exercises, problems, and solutions are found throughout. Also, a related website features additional exercises with solutions and supplementary material for classroom use. Introduction to Probability and Stochastic Processes with Applications is an ideal book for probability courses at the upper-undergraduate level. The book is also a valuable reference for researchers and practitioners in the fields of engineering, operations research, and computer science who conduct data analysis to make decisions in their everyday work.

Probability and Stochastic Processes

Author : Ionut Florescu
Publisher : John Wiley & Sons
ISBN 13 : 0470624558
Total Pages : 578 pages
Book Rating : 4.4/5 (76 download)

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Book Synopsis Probability and Stochastic Processes by : Ionut Florescu

Download or read book Probability and Stochastic Processes written by Ionut Florescu and published by John Wiley & Sons. This book was released on 2014-10-27 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 format. The book’s primary focus is on key theoretical notions in probability to provide a foundation for understanding concepts and examples related to stochastic processes. Organized into two main sections, the book begins by developing probability theory with topical coverage on probability measure; random variables; integration theory; product spaces, conditional distribution, and conditional expectations; and limit theorems. The second part explores stochastic processes and related concepts including the Poisson process, renewal processes, Markov chains, semi-Markov processes, martingales, and Brownian motion. Featuring a logical combination of traditional and complex theories as well as practices, Probability and Stochastic Processes also includes: Multiple examples from disciplines such as business, mathematical finance, and engineering Chapter-by-chapter exercises and examples to allow readers to test their comprehension of the presented material A rigorous treatment of all probability and stochastic processes concepts An appropriate textbook for probability and stochastic processes courses at the upper-undergraduate and graduate level in mathematics, business, and electrical engineering, Probability and Stochastic Processes is also an ideal reference for researchers and practitioners in the fields of mathematics, engineering, and finance.