Description

This course provides an introduction to the the theory of stochastic processes with emphasis on applications.

Prerequisites

Courses in graduate probability and undergraduate real analysis or authorisation by the instructor.

References

• Probability and random processes, 3rd ed., by Grimmett and Stirzaker. Oxford
• A first look at rigorous probability theory by Rosenthal.
• Stochastic calculus for finance II: continuous time models by Sherve.
• A first course in stochastic processes by Karlin and Taylor.
• Stochastic Processes by Lawler.
• Stochastic modeling of scientific data by Perer Gutrop.