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