期刊
JOURNAL OF STATISTICAL THEORY AND PRACTICE
卷 5, 期 2, 页码 221-229出版社
TAYLOR & FRANCIS AS
DOI: 10.1080/15598608.2011.10412025
关键词
Censored data; Density estimation; Kaplan-Meier estimator; Kernel Smoothing
It has long been recognized that accurate estimation of the density function is an important problem for inference with censored data (see Gehan, 1969). This paper presents a new kernel type estimator, which smooths at observed lifetimes inversely proportional to their density according to Abramson's square root law. It is shown that a similar reduction in bias is achieved.
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