Stochastic Modeling

Stochastic Modeling
Author :
Publisher : Springer
Total Pages : 305
Release :
ISBN-10 : 9783319500386
ISBN-13 : 3319500384
Rating : 4/5 (384 Downloads)

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 305 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.


Stochastic Modeling Related Books

Stochastic Modeling
Language: en
Pages: 305
Authors: Nicolas Lanchier
Categories: Mathematics
Type: BOOK - Published: 2017-01-27 - Publisher: Springer

DOWNLOAD EBOOK

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 reade
An Introduction to Stochastic Modeling
Language: en
Pages: 410
Authors: Howard M. Taylor
Categories: Mathematics
Type: BOOK - Published: 2014-05-10 - Publisher: Academic Press

DOWNLOAD EBOOK

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich d
Stochastic Modeling
Language: en
Pages: 338
Authors: Barry L. Nelson
Categories: Mathematics
Type: BOOK - Published: 2012-10-11 - Publisher: Courier Corporation

DOWNLOAD EBOOK

Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models
Markov Processes for Stochastic Modeling
Language: en
Pages: 515
Authors: Oliver Ibe
Categories: Mathematics
Type: BOOK - Published: 2013-05-22 - Publisher: Newnes

DOWNLOAD EBOOK

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
Stochastic Modelling of Reaction–Diffusion Processes
Language: en
Pages: 322
Authors: Radek Erban
Categories: Mathematics
Type: BOOK - Published: 2020-01-30 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

This practical introduction to stochastic reaction-diffusion modelling is based on courses taught at the University of Oxford. The authors discuss the essence o