Event Detail

Event Type: 
Wednesday, August 4, 2021 - 14:00 to 16:00
Zoom - If you are interested in attending this presentation, please send an email to Nikki Sullivan - nikki.sullivan@oregonstate.edu - to request Zoom log in details.

Stein’s method initially introduced in 1970 by C. Stein is a powerful technique for bounding the distance between the laws of two real-valued random variables. Stein’s method has been used to prove distributional convergence to many standard probability distribu- tions such as normal, multivariate normal, Poisson and Brownian motion approximation. In 1990, A.D. Barbour developed Stein’s method and gave an alternative poof of the functional central limit theorem. In this dissertation, we use Stein’s method developed by Barbour to reprove Liggett’s functional central limit theorem. We also reprove the Newman’s central limit theorem using Stein’s method.