Upcoming Events
-
9/27
Social Psychology Speaker Series
Social Psychology Speaker Series
Wednesday, September 27th, 2023
02:00 PM - 03:15 PM
Bousfield Building
Dr. Flora Oswald, University of Connecticut
Social perceptions and experiences among marginalized group members: Implications for intergroup disparities
-
9/27
STAT Colloquium, Prof. Sujit K. Ghosh
STAT Colloquium, Prof. Sujit K. Ghosh
Wednesday, September 27th, 2023
04:00 PM - 05:00 PM
Austin Building
Professor Sujit K. Ghosh, Ph.D.
Department of Statistics
North Carolina State UniversityRecipient of the 2023 UConn Statistics Department
Distinguished Alumnus AwardNonparametric Estimation of Multivariate Copula using Empirical Bayes Method
In the field of finance, insurance, and system reliability, etc., it is often of interest to measure the dependence among variables by modeling a multivariate distribution using a copula. The copula models with parametric assumptions are easy to estimate but can be highly biased when such assumptions are false, while the empirical copulas are non-smooth and often not genuine copula, making the inference about dependence challenging in practice. As a compromise, the empirical Bernstein copula provides a smooth estimator, but the estimation of tuning parameters remains elusive. In this paper, by using the so-called empirical checkerboard copula, we build a hierarchical empirical Bayes model that enables the estimation of a smooth copula function for arbitrary dimensions. The proposed estimator based on the multivariate Bernstein polynomials is itself a genuine copula, and the selection of its dimension-varying degrees is data-dependent. We also show that the proposed copula estimator provides a more accurate estimate of several multivariate dependence measures, which can be obtained in closed form. We investigate the asymptotic and finite-sample performance of the proposed estimator and compare it with some nonparametric estimators through simulation studies. An application to portfolio risk management is presented, along with a quantification of estimation uncertainty. [This presentation is based on a joint work with my former student Dr. Lu Lu]
DATE: Wednesday, September 27, 2023
TIME: 4:00 pm
PLACE: AUST 110
WebEx: https://uconn-cmr.webex.com/uconn-cmr/j.php?MTID=m44f5da414545274b83c84dec11d638d5
Coffee will be served 3:30-4:00 in the Noether Lounge (AUST 326) -
9/29
Linguistics Colloquium Series
Linguistics Colloquium Series
Friday, September 29th, 2023
02:00 PM - 04:00 PM
Online
Philippe Schlenker