Title

Optimal Goodness-of-fit Tests for Recurrent Event Data

Abstract

A class of tests for the hypothesis that the baseline intensity belongs to a parametric class of intensities is given in the recurrent event setting. Asymptotic properties of a weighted general class of processes that compare the non-parametric versus parametric estimators for the cumulative intensity are presented. These results are given for a sequence of Pitman alternatives. Test statistics are proposed and methods of obtaining critical values are examined. Optimal choices for the weight function are given for a class of chi-squared tests. Based on Khmaladze's transformation we propose distributional free tests. These include the types of Kolmogorov-Smirnov and Cramér-von Mises. The tests are used to analyze two different data sets.

Department(s)

Mathematics and Statistics

Keywords and Phrases

counting processes; effective age; khmaladze's transformation; martingales; stochastic integration

Library of Congress Subject Headings

Goodness-of-fit tests

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2011 Springer Verlag, All rights reserved.

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