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.

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