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+<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>
+<WRAP 70% center>
+^  **DATE:**|Thursday, April 14, 2022 |
+^  **TIME:**|1:15pm -- 2:15pm |
+^  **LOCATION:**|Zoom meeting |
+^  **SPEAKER:**|Zifan Huang, Binghamton  University |
+^  **TITLE:**|The Maximum Likelihood Estimator Under The Uniform Distribution With Linear Regression Data  (His ABD exam)|
+</WRAP>
+\\
+<WRAP center box 80%>
+<WRAP centeralign>**Abstract**</WRAP>
+In research and statistics projects, if we know the form of the
+regression, parametric inferences often perform better than semiparametric
+inferences and nonparametric inferences. This talk focus on the maximum
+likelihood estimator (MLE) under the uniform distribution with linear
+regression data. We first introduce and discuss the assumptions and the
+conclusions in Robbins, H. and Zhang, C.-H.'s paper. Then we develop
+the closed form algorithm to find the MLE under the multiple linear
+regression model. Some results on this subject with the simple linear
+regression and non-random covariate are introduced and compared.
+</WRAP>