The Empirical Distribution Function with Arbitrarily Grouped, Censored and Truncated Data
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ID: 291460
1976
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Abstract
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.
| Reference Key |
openalex_W2121493622
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|---|---|
| Authors | Bruce W. Turnbull |
| Journal | Journal of the Royal Statistical Society Series B (Statistical Methodology) |
| Year | 1976 |
| DOI |
10.1111/j.2517-6161.1976.tb01597.x
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| URL | |
| Keywords | Keywords not found |
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