论文信息 - The Empirical Distribution Function with Arbitrarily Grouped, Censored, and Truncated Data

The Empirical Distribution Function with Arbitrarily Grouped, Censored, and Truncated Data

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.

B. Turnbull

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