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A First Look At Stochastic Processes by Jeffrey S Rosenthal: New

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Book Title
A First Look At Stochastic Processes
Publication Date
2019-10-04
ISBN
9789811208973

Über dieses Produkt

Product Identifiers

Publisher
World Industries Scientific Publishing Co Pte LTD
ISBN-10
9811208972
ISBN-13
9789811208973
eBay Product ID (ePID)
9038575620

Product Key Features

Number of Pages
200 Pages
Language
English
Publication Name
First Look at Stochastic Processes
Publication Year
2020
Subject
Probability & Statistics / Stochastic Processes, Probability & Statistics / Regression Analysis
Type
Textbook
Author
Jeffrey S. Rosenthal
Subject Area
Mathematics
Format
Trade Paperback

Additional Product Features

Intended Audience
Trade
LCCN
2019-044552
Dewey Edition
23
TitleLeading
A
Illustrated
Yes
Dewey Decimal
519.23
Synopsis
This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mathematical results through simple, clear, logical theorems and examples. It covers in detail such essential material as Markov chain recurrence criteria, the Markov chain convergence theorem, and optional stopping theorems for martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and renewal theory.Interspersed throughout are applications to such topics as gambler's ruin probabilities, random walks on graphs, sequence waiting times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as well-motivated and accessible as possible, to allow students and readers to learn this fascinating subject as easily and painlessly as possible., This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mathematical results through simple, clear, logical theorems and examples. It covers in detail such essential material as Markov chain recurrence criteria, the Markov chain convergence theorem, and optional stopping theorems for martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and renewal theory. Interspersed throughout are applications to such topics as gambler's ruin probabilities, random walks on graphs, sequence waiting times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms. The focus is always on making the theory as well-motivated and accessible as possible, to allow students and readers to learn this fascinating subject as easily and painlessly as possible., This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mathematical results through simple, clear, logical theorems and examples. It covers in detail such essential material as Markov chain recurrence criteria, the Markov chain convergence theorem, and optional stopping theorems for martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and/or space, Poisson processes, and renewal theory.Interspersed throughout are applications to such topics as gambler's ruin probabilities, random walks on graphs, sequence waiting times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as well-motivated and accessible as possible, to allow students and readers to learn this amazing subject as easily and painlessly as possible.

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