Applied Stochastic Modeling

✍ Scribed by Liliana Blanco-Castañeda, Viswanathan Arunachalam

Publisher: Springer
Year: 2023
Tongue: English
Leaves: 154
Series: Synthesis Lectures on Mathematics & Statistics
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book provides the essential theoretical tools for stochastic modeling. The authors address the most used models in applications such as Markov chains with discrete-time parameters, hidden Markov chains, Poisson processes, and birth and death processes. This book also presents specific examples with simulation methods that apply the topics to different areas of knowledge. These examples include practical applications, such as modeling the COVID-19 pandemic and animal movement modeling. This book is concise and rigorous, presenting the material in an easily accessible manner that allows readers to learn how to address and solve problems of a stochastic nature.

✦ Table of Contents

Preface
Contents
1 Discrete-Time Markov Chain
2 Poisson Processes and Its Extensions
3 Continuous-Time Markov Chain Modeling
4 Branching Processes
5 Hidden Markov Model
Appendix A
Index

📜 SIMILAR VOLUMES

Stochastic Calculus and Financial Applic

📁 Stochastic Calculus and Financial Applications (Stochastic Modelling and Applied Probability 45)

✍ J. Michael Steele 📂 Library 📅 2000 🏛 Springer 🌐 English

Stochastic calculus has important applications to mathematical finance. This book will appeal to practitioners and students who want an elementary introduction to these areas. From the reviews: "As the preface says, ‘This is a text with an attitude, and it is designed to reflect, wherever possible a

Stochastic Models in Reliability (Stocha

📁 Stochastic Models in Reliability (Stochastic Modelling and Applied Probability)

✍ Terje Aven, Uwe Jensen 📂 Library 📅 1999 🌐 English

A comprehensive up-to-date presentation of some of the classical areas of reliability, based on a more advanced probabilistic framework using the modern theory of stochastic processes. This framework allows analysts to formulate general failure models, establish formulae for computing various perfor

Applied Stochastic System Modeling

📁 Applied Stochastic System Modeling

✍ Professor Dr. Shunji Osaki (auth.) 📂 Library 📅 1992 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

<p>This book was written for an introductory one-semester or two-quarter course in stochastic processes and their applications. The reader is assumed to have a basic knowledge of analysis and linear algebra at an undergraduate level. Stochastic models are applied in many fields such as engineering s

Stochastic Portfolio Theory (Stochastic

📁 Stochastic Portfolio Theory (Stochastic Modelling and Applied Probability)

✍ E. Robert Fernholz 📂 Library 📅 2002 🏛 Springer 🌐 English

Stochastic portfolio theory is a mathematical methodology for constructing stock portfolios and for analyzing the effects induced on the behavior of these portfolios by changes in the distribution of capital in the market. Stochastic portfolio theory has both theoretical and practical applications:

Applied Stochastic Modelling, Second Edi

📁 Applied Stochastic Modelling, Second Edition

✍ Byron J T Morgan 📂 Library 📅 2017 🏛 CRC Press 🌐 English

Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statisti

Introduction to Stochastic Calculus Appl

📁 Introduction to Stochastic Calculus Applied to Finance (Stochastic Modeling)

✍ Damien Lamberton, Bernard Lapeyre, 📂 Library 📅 1996 🌐 English

In recent years the growing importance of derivative products financial markets has increased financial institutions' demands for mathematical skills. This book introduces the mathematical methods of financial modeling with clear explanations of the most useful models. Introduction to Stochastic Cal