This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 458
Type: Topic Contributed
Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #307277
Title: Nonparametric Estimation of Time Trend for Recurrent Events Data
Author(s): Bo Henry Lindqvist*+
Companies: Norwegian University of Science and Technology
Address: Department of Mathematical Sciences, Trondheim, 7491, Norway
Keywords: Trend-Renewal Process ; Kernel Estimator

The trend-renewal-process (TRP) is defined to be a time-transformed renewal process, where the time transformation is given by a trend function which is similar to the intensity of a nonhomogeneous Poisson process (NHPP). A nonparametric maximum likelihood estimator of the trend function of a TRP can be obtained in principle in a similar manner as for the NHPP using kernel smoothing. But for a TRP one must consider the simultaneous estimation of the renewal distribution, which is here assumed to belong to a parametric class such as the Weibull-distribution. A weighted kernel estimator for the trend function is suggested and studied.

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