Softcover ISBN:  9781470465698 
Product Code:  GSM/199.S 
List Price:  $89.00 
MAA Member Price:  $80.10 
AMS Member Price:  $71.20 
eBook ISBN:  9781470452414 
EPUB ISBN:  9781470476571 
Product Code:  GSM/199.E 
List Price:  $75.00 
MAA Member Price:  $67.50 
AMS Member Price:  $60.00 
Softcover ISBN:  9781470465698 
eBook: ISBN:  9781470452414 
Product Code:  GSM/199.S.B 
List Price:  $164.00 $126.50 
MAA Member Price:  $147.60 $113.85 
AMS Member Price:  $131.20 $101.20 
Softcover ISBN:  9781470465698 
Product Code:  GSM/199.S 
List Price:  $89.00 
MAA Member Price:  $80.10 
AMS Member Price:  $71.20 
eBook ISBN:  9781470452414 
EPUB ISBN:  9781470476571 
Product Code:  GSM/199.E 
List Price:  $75.00 
MAA Member Price:  $67.50 
AMS Member Price:  $60.00 
Softcover ISBN:  9781470465698 
eBook ISBN:  9781470452414 
Product Code:  GSM/199.S.B 
List Price:  $164.00 $126.50 
MAA Member Price:  $147.60 $113.85 
AMS Member Price:  $131.20 $101.20 

Book DetailsGraduate Studies in MathematicsVolume: 199; 2019; 305 ppMSC: Primary 60; 62; 65; 82
This is a textbook for advanced undergraduate students and beginning graduate students in applied mathematics. It presents the basic mathematical foundations of stochastic analysis (probability theory and stochastic processes) as well as some important practical tools and applications (e.g., the connection with differential equations, numerical methods, path integrals, random fields, statistical physics, chemical kinetics, and rare events). The book strikes a nice balance between mathematical formalism and intuitive arguments, a style that is most suited for applied mathematicians. Readers can learn both the rigorous treatment of stochastic analysis as well as practical applications in modeling and simulation. Numerous exercises nicely supplement the main exposition.
ReadershipUndergraduate and graduate students and researchers interested in stochastic processes, stochastic analysis, and applications.

Table of Contents

Fundamentals

Random variables

Limit theorems

Markov chains

Monte Carlo methods

Stochastic processes

Wiener process

Stochastic differential equations

FokkerPlanck equation

Advanced topics

Path integral

Random fields

Introduction to statistical mechanics

Rare events

Introduction to chemical reaction kinetics


Additional Material

Reviews

This book strikes a nice balance between mathematical formalism and intuitive arguments; a style that is most suited for applied mathematicians. Readers can learn both the rigorous treatment of stochastic analysis as well as practical applications in modeling and simulation.
Peter Rabinovitch, MAA Reviews


RequestsReview Copy – for publishers of book reviewsDesk Copy – for instructors who have adopted an AMS textbook for a courseExamination Copy – for faculty considering an AMS textbook for a coursePermission – for use of book, eBook, or Journal contentAccessibility – to request an alternate format of an AMS title
 Book Details
 Table of Contents
 Additional Material
 Reviews
 Requests
This is a textbook for advanced undergraduate students and beginning graduate students in applied mathematics. It presents the basic mathematical foundations of stochastic analysis (probability theory and stochastic processes) as well as some important practical tools and applications (e.g., the connection with differential equations, numerical methods, path integrals, random fields, statistical physics, chemical kinetics, and rare events). The book strikes a nice balance between mathematical formalism and intuitive arguments, a style that is most suited for applied mathematicians. Readers can learn both the rigorous treatment of stochastic analysis as well as practical applications in modeling and simulation. Numerous exercises nicely supplement the main exposition.
Undergraduate and graduate students and researchers interested in stochastic processes, stochastic analysis, and applications.

Fundamentals

Random variables

Limit theorems

Markov chains

Monte Carlo methods

Stochastic processes

Wiener process

Stochastic differential equations

FokkerPlanck equation

Advanced topics

Path integral

Random fields

Introduction to statistical mechanics

Rare events

Introduction to chemical reaction kinetics

This book strikes a nice balance between mathematical formalism and intuitive arguments; a style that is most suited for applied mathematicians. Readers can learn both the rigorous treatment of stochastic analysis as well as practical applications in modeling and simulation.
Peter Rabinovitch, MAA Reviews