English | 2022 | ISBN: 1032153733 , 978-1118740651 | 201 pages | True PDF | 5.96 MB
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 familiarise themselves with stochastic processes before going onto 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.
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