Estimation of the hazard function when the data are censored is an important problem in medical research. In this article, we propose a simple non-parametric estimator of the hazard function. Its asymptotic properties are derived, and numerical comparisons with other existing estimators are made. The proposed estimator is shown to be at least as good as the other estimators from both the theoretical and the numerical points of view.
机构:
Aventis Pharma Ltd, Biostat & Data Management Dept, Minato Ku, Tokyo 1078465, JapanAventis Pharma Ltd, Biostat & Data Management Dept, Minato Ku, Tokyo 1078465, Japan
Nishikawa, M
Tango, T
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机构:
Aventis Pharma Ltd, Biostat & Data Management Dept, Minato Ku, Tokyo 1078465, JapanAventis Pharma Ltd, Biostat & Data Management Dept, Minato Ku, Tokyo 1078465, Japan