The Empirical Distribution Function with Arbitrarily Grouped, Censored, and Truncated Data
The Empirical Distribution Function with Arbitrarily Grouped, Censored, and Truncated Data
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DOI：
10.1111/j.2517-6161.1976.tb01597.x
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发表时间：
1976-07
期刊：
影响因子：
--
通讯作者：
B. Turnbull
中科院分区：
文献类型：
--
作者：
B. Turnbull
摘要本文讨论了当数据由于分组、截尾和/或截断而不完整时，分布函数F的非参数估计。利用自相容性的思想，构造了一个简单的算法，并证明该算法单调收敛，从而得到F的最大似然估计。假设检验的应用表明。
SUMMARY This paper is concerned with the non-parametric estimation of a distribution function F, when the data are incomplete due to grouping, censoring and/or truncation. Using the idea of self-consistency, a simple algorithm is constructed and shown to converge monotonically to yield a maximum likelihood estimate of F. An application to hypothesis testing is indicated.