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--- seminars:stat:220421 [2022/04/09 11:59] – qyu
+++ seminars:stat:220421 [2022/04/14 23:05] (current) – qyu
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+<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>
+<WRAP 70% center>
+^  **DATE:**|Thursday, April 21, 2022 |
+^  **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>Bivariate data where the marginal distributions differ by a
+location and
+scale parameter are considered. Inference about these two parameters
+is based on the empirical likelihood approach. As the first component and
+the location and scale transformed second component have the same
+distribution, there is a large supply of constraint functions. Both known
+and estimated constraint functions are studied. Wilks' type theorems are
+obtained for these settings leading to large sample confidence regions and
+tests. The local asymptotic power of the resulting tests is derived.
+Finally maximum empirical likelihood estimators of the location and scale
+parameters are studied and shown to be asymptotically normal. An extensive
+simulation study supports the theoretical findings.
+</WRAP>