Stochastic Processes with R Stochastic Processes with R
Chapman & Hall/CRC Texts in Statistical Science

Stochastic Processes with R

An Introduction

    • $59.99
    • $59.99

Publisher Description

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. The light yet detailed text provides a solid foundation that is an ideal companion for undergraduate statistics students looking to familiarize themselves with stochastic processes before going on to more advanced courses.

Key Features Provides complete R codes for all simulations and calculations Substantial scientific or popular applications of each process with occasional statistical analysis Helpful definitions and examples are provided for each process End of chapter exercises cover theoretical applications and practice calculations

GENRE
Science & Nature
RELEASED
2022
February 16
LANGUAGE
EN
English
LENGTH
200
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
17.6
MB
Essentials of Stochastic Processes Essentials of Stochastic Processes
2012
Simulation Simulation
2006
Bayesian Inference for Stochastic Processes Bayesian Inference for Stochastic Processes
2017
Basic Probability Theory with Applications Basic Probability Theory with Applications
2009
Probability and Simulation Probability and Simulation
2020
Stochastic Models in the Life Sciences and Their Methods of Analysis Stochastic Models in the Life Sciences and Their Methods of Analysis
2019
Statistical Rethinking Statistical Rethinking
2020
Introduction to Probability, Second Edition Introduction to Probability, Second Edition
2019
Sampling Sampling
2021
Statistical Inference Statistical Inference
2024
Bayes Rules! Bayes Rules!
2022
Bayesian Modeling and Computation in Python Bayesian Modeling and Computation in Python
2021