Differences

This shows you the differences between two versions of the page.

--- seminars:datasci:191105 [2019/10/28 16:23] – created sdang
+++ seminars:datasci:191105 [2019/11/04 18:12] (current) – qyu
@@ Line 1: / Line 1: @@
+<WRAP centeralign>##Data Science Seminar##\\ Hosted by Department of Mathematical Sciences</WRAP>
+  * Date: Tuesday, Nov 5, 2019
+  * Time: 12:00pm -- 1:00pm
+  * Room: WH-100E
+  * Speaker: Wangshu Tu (Binghamton University)
+  * Title: Non existence of fixed sample estimator for prescribed proportional closeness
+<WRAP center box 80%>
+<WRAP centeralign>**//Abstract//**</WRAP>
+Proportional closeness is a common practice in engineering and applied
+sciences. It asks for an estimator of a parameter of a statistical
+distribution which, with high probability, does not deviate from the value
+of the parameter by more than a certain percentage of its absolute
+value(Zacks 1966). If x is a parameter of consideration, we can write
+proportional closeness as P(|x^-x|<d|x|)> r, where d and r are in (0,1).
+In this talk, we will prove that there is no fixed sample estimator,
+satisfy above inequality for all x.
+</WRAP>