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.

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.

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.

Markov Processes for Stochastic Modeling

Author : Oliver Ibe
Publisher : Newnes
ISBN 13 : 0124078397
Total Pages : 514 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Markov Processes for Stochastic Modeling by : Oliver Ibe

Download or read book Markov Processes for Stochastic Modeling written by Oliver Ibe and published by Newnes. This book was released on 2013-05-22 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. Presents both the theory and applications of the different aspects of Markov processes Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.

Stochastic Modeling

Author :
Publisher :
ISBN 13 : 9780981396811
Total Pages : pages
Book Rating : 4.3/5 (968 download)

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Book Synopsis Stochastic Modeling by :

Download or read book Stochastic Modeling written by and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

Stochastic Models with Power-Law Tails

Author : Dariusz Buraczewski
Publisher : Springer
ISBN 13 : 3319296795
Total Pages : 320 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Stochastic Models with Power-Law Tails by : Dariusz Buraczewski

Download or read book Stochastic Models with Power-Law Tails written by Dariusz Buraczewski and published by Springer. This book was released on 2016-07-04 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph the authors give a systematic approach to the probabilistic properties of the fixed point equation X=AX+B. A probabilistic study of the stochastic recurrence equation X_t=A_tX_{t-1}+B_t for real- and matrix-valued random variables A_t, where (A_t,B_t) constitute an iid sequence, is provided. The classical theory for these equations, including the existence and uniqueness of a stationary solution, the tail behavior with special emphasis on power law behavior, moments and support, is presented. The authors collect recent asymptotic results on extremes, point processes, partial sums (central limit theory with special emphasis on infinite variance stable limit theory), large deviations, in the univariate and multivariate cases, and they further touch on the related topics of smoothing transforms, regularly varying sequences and random iterative systems. The text gives an introduction to the Kesten-Goldie theory for stochastic recurrence equations of the type X_t=A_tX_{t-1}+B_t. It provides the classical results of Kesten, Goldie, Guivarc'h, and others, and gives an overview of recent results on the topic. It presents the state-of-the-art results in the field of affine stochastic recurrence equations and shows relations with non-affine recursions and multivariate regular variation.

Stochastic Modelling for Systems Biology

Author : Darren J. Wilkinson
Publisher : CRC Press
ISBN 13 : 9781584885405
Total Pages : 296 pages
Book Rating : 4.8/5 (854 download)

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Book Synopsis Stochastic Modelling for Systems Biology by : Darren J. Wilkinson

Download or read book Stochastic Modelling for Systems Biology written by Darren J. Wilkinson and published by CRC Press. This book was released on 2006-04-18 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks, most researchers in the field have limited knowledge of stochastic process theory. The stochastic processes formalism provides a beautiful, elegant, and coherent foundation for chemical kinetics and there is a wealth of associated theory every bit as powerful and elegant as that for conventional continuous deterministic models. The time is right for an introductory text written from this perspective. Stochastic Modelling for Systems Biology presents an accessible introduction to stochastic modelling using examples that are familiar to systems biology researchers. Focusing on computer simulation, the author examines the use of stochastic processes for modelling biological systems. He provides a comprehensive understanding of stochastic kinetic modelling of biological networks in the systems biology context. The text covers the latest simulation techniques and research material, such as parameter inference, and includes many examples and figures as well as software code in R for various applications. While emphasizing the necessary probabilistic and stochastic methods, the author takes a practical approach, rooting his theoretical development in discussions of the intended application. Written with self-study in mind, the book includes technical chapters that deal with the difficult problems of inference for stochastic kinetic models from experimental data. Providing enough background information to make the subject accessible to the non-specialist, the book integrates a fairly diverse literature into a single convenient and notationally consistent source.

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

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.

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 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.

Stochastic Modeling

Author : Hossein Bonakdari
Publisher : Elsevier
ISBN 13 : 0323972756
Total Pages : 372 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Stochastic Modeling by : Hossein Bonakdari

Download or read book Stochastic Modeling written by Hossein Bonakdari and published by Elsevier. This book was released on 2022-04-13 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Modeling: A Thorough Guide to Evaluate, Pre-Process, Model and Compare Time Series with MATLAB Software allows for new avenues in time series analysis and predictive modeling which summarize more than ten years of experience in the application of stochastic models in environmental problems. The book introduces a variety of different topics in time series in the modeling and prediction of complex environmental systems. Most importantly, all codes are user-friendly and readers will be able to use them for their cases. Users who may not be familiar with MATLAB software can also refer to the appendix. This book also guides the reader step-by-step to learn developed codes for time series modeling, provides required toolboxes, explains concepts, and applies different tools for different types of environmental time series problems. Provides video tutorials on the use of codes Includes a companion site with 3,000 lines of programming, 70 principal codes and 100 pseudo codes Highlights multiple methods to Illustrate each problem

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.

Stochastic Modelling of Reaction–Diffusion Processes

Author : Radek Erban
Publisher : Cambridge University Press
ISBN 13 : 1108572995
Total Pages : 322 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis Stochastic Modelling of Reaction–Diffusion Processes by : Radek Erban

Download or read book Stochastic Modelling of Reaction–Diffusion Processes written by Radek Erban and published by Cambridge University Press. This book was released on 2020-01-30 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction to stochastic reaction-diffusion modelling is based on courses taught at the University of Oxford. The authors discuss the essence of mathematical methods which appear (under different names) in a number of interdisciplinary scientific fields bridging mathematics and computations with biology and chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate or beginning graduate-level courses in applied mathematics. New mathematical approaches are explained using simple examples of biological models, which range in size from simulations of small biomolecules to groups of animals. The book starts with stochastic modelling of chemical reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio-temporal models are then studied, including models of diffusion and stochastic reaction-diffusion modelling. The methods covered include molecular dynamics, Brownian dynamics, velocity jump processes and compartment-based (lattice-based) models.

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 Modeling and the Theory of Queues

Author : Ronald W. Wolff
Publisher : Pearson
ISBN 13 :
Total Pages : 580 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Stochastic Modeling and the Theory of Queues by : Ronald W. Wolff

Download or read book Stochastic Modeling and the Theory of Queues written by Ronald W. Wolff and published by Pearson. This book was released on 1989 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated and up-to-date treatment of applied stochastic processes and queueing theory, with an emphasis on time-averages and long-run behavior. Theory demonstrates practical effects, such as priorities, pooling of queues, and bottlenecks. Appropriate for senior/graduate courses in queueing theory in Operations Research, Computer Science, Statistics, or Industrial Engineering departments. (vs. Ross, Karlin, Kleinrock, Heyman)