Stochastic Processes With R - An Introduction

Stochastic Processes with R: An Introduction cuts through the heavy theory that is present in most courses on random processes and serves as practical guide to simulated trajectories and real-life applications for stochastic processes.

List of contents

1 Stochastic Process. Discrete-time Markov Chain 2 Random Walk 3 Poisson Process 4 Nonhomogeneous Poisson Process 5 Compound Poisson Process 6 Conditional Poisson Process 7 Birth-and-Death Process 8 Branching Process 9 Brownian Motion

About the author

Olga Korosteleva, PhD, is a professor of statistics in the Department of Mathematics and Statistics at California State University, Long Beach (CSULB). She earned her Bachelor’s degree in mathematics in 1996 from Wayne State University in Detroit, and her PhD in statistics from Purdue University in West Lafayette, Indiana, in 2002. Since then she has been teaching statistics and mathematics courses at CSULB.

Summary

Stochastic Processes with R: An Introduction cuts through the heavy theory that is present in most courses on random processes and serves as practical guide to simulated trajectories and real-life applications for stochastic processes.

Product details

• Authors: Olga Korosteleva, Olga (California State University Korosteleva, Korosteleva Olga
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 27.05.2024
• EAN: 9781032154732
• ISBN: 978-1-0-3215473-2
• No. of pages: 190
• Series: Chapman & Hall/CRC Texts in Statistical Science
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; MATHEMATICS / Probability & Statistics / General, Probability & statistics, Probability and statistics