Tuesday, Nov 8, 2016 - 3:30pm - Allen 14
Statistics seminar
A Pearson chi-square hypothesis testing for hazard rate
Ralph Vital, Statistics, Msstate

Title:  A Pearson chi-square hypothesis testing for hazard rate
Abstract:  In the literature there exists, many hypothesis testing to conclude whether or not a sample data is from a parametric hazard rate function, say : h0. The log-rank, the Herrington and Fleming, and the Tarone-Ware test divide the range of the hazard function into class intervals, and lead to hazard function estimates that are constant over each interval. However, we know that a better measurement for the discrepancy between the estimated and the true function is the integrated square error (ISE). Our work is to develop a non parametric (smoothing-based) test lack-of-fit for the hazard rate function based on the Integrated Square Error. To begin with, we are investigating the conditions for a Pearson chi-square test for hazard rate function.

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