
<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>

<WRAP 70% center>
^  **DATE:**|Thursday, April 1, 2021 |
^  **TIME:**|1:15pm -- 2:15pm |
^  **LOCATION:**|Zoom meeting |
^  **SPEAKER:**|Mengyu Chen, Binghamton University |
^  **TITLE:**|An Empirical Likelihood Approach with Bivariate Data  |
</WRAP>
\\ 

<WRAP center box 80%>
<WRAP centeralign>**Abstract**</WRAP>
Consider a random sample from a bivariate random vector
whose marginal distributions differ by a location parameter.
An empirical likelihood approach with a fixed number of unknown
constraints is proposed.  A Wilks’ type theorem is derived,
including the construction of a non-parametric confidence region and test.
Then a uniform local asymptotic normality condition is established
for the empirical likelihood. This is used to derive various versions
of maximum empirical likelihood estimators based on the work of
Peng and Schick (2018).

This is the Admission to Candidacy Exam for Mengyu Chen.
The Committee members are Guifang Fu, Anton Schick (Chair),
and Qiqing Yu.
</WRAP>