Differences

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

--- seminars:stat:141113 [2014/09/25 20:40] – created qiao
+++ seminars:stat:141113 [2014/10/07 15:13] (current) – qyu
@@ Line 1: / Line 1: @@
+<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>
+~~META:title =November 13, 2014~~
+<WRAP 70% center>
+|  **DATE:**|Thursday, November 13, 2014 |
+|  **TIME:**|1:15pm to 2:15pm |
+|  **PLACE:**|OW 100E |
+|  **SPEAKER:**| Withanage A. De Mel (Binghamton University) |
+|  **TITLE:**|Chi-Squared Goodness of Fit Test Based on Random Cells with Recurrent Event Data  |
+</WRAP>
+\\
+<WRAP center box 80%>
+<WRAP centeralign>**Abstract**</WRAP>We consider a recurrent event wherein the inter-event time distribution $F$ is assumed to belong to some parametric family of the distributions $\mathcal{F},$ where the unknown parameter $\theta$ is $q$-dimensional. This work deals with the problem of goodness-of-fit test for $F.$ We develop a chi-square type test where the $k$ nonoverlapping cell boundaries are randomly chosen. Our test used a Kaplan Meier type nonparametric maximum likelihood estimator (NPMLE) of $F$ to obtain the observed frequencies. The minimum distance estimator of $\theta$ is obtained by minimizing the quadratic form that resulted from the properly scaled vector of differences between the observed and expected cell frequencies. The proposed chi-square test statistic is constructed by using the NPMLE of $F$ and the minimum distance estimator. We show that the proposed test statistic is asymptotically chi-square with $k - q -1$ degrees of freedom. Results for specific families of distributions such as Weibull and Exponential are presented. We also discuss results of a simulation study as well as application to a biomedical data set.
+</WRAP>