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- W2040341664 abstract "Let $X_1, X_2, ldots$ be a sequence of i.i.d. random variables with d.f. $F$. We observe $Z_i = min(X_i,Y_i)$ and $delta_i = 1_{{X_i leq Y_i}}$, where $Y_1, Y_2, ldots$ is a sequence of i.i.d. censoring random variables. Denote by $hat{F}_n$ the Kaplan-Meier estimator of $F$. We show that for any $F$-integrable function $varphi, intvarphi dhat{F}_n$ converges almost surely and in the mean. The result may be applied to yield consistency of many estimators under random censorship." @default.
- W2040341664 created "2016-06-24" @default.
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- W2040341664 date "1993-09-01" @default.
- W2040341664 modified "2023-10-06" @default.
- W2040341664 title "The Strong Law under Random Censorship" @default.
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- W2040341664 doi "https://doi.org/10.1214/aos/1176349273" @default.
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