STATISTICS COLLOQUIUM
Zhiyi Chi, Professor
Department of Statistics
University of Connecticut
Exact sampling for infinitely divisible distributions and Levy processes
Abstract
Infinitely divisible (i.d.) distributions have many applications. Unfortunately, many of them are specified via sum of infinitely many jumps and have no closed-form expressions, making them difficult to sample exactly. I will show that for a rather wide range of i.d. distributions with finite variation, this difficulty can be overcome by utilizing an integral series expansion of their probability densities and rejection sampling.
If time permits, I will also briefly discusses exact sampling of first passage event of Levy processes. The idea is to embed a process into a ``carrier'' process whose first passage event can be sampled exactly and then extract the part belonging to the former from the data sampled for the carrier. This part will be mostly explained by pictures instead of technical formulas.
DATE: Wednesday, September 13, 2017
TIME: 4:00 pm
PLACE: Philip E. Austin Bldg., Rm. 105
Coffee will be served at 3:30 pm in the Noether Lounge (AUST 326)
For more information, contact: Tracy Burke at tracy.burke@uconn.edu