Abstract
Doubly truncated data appear in a number of applications, including astronomy and survival analysis. For double-truncated data, the lifetime T is observable only when U≤T≤V, where U and V are the left-truncated and right-truncated time, respectively. In some situations, the lifetime T also suffers interval censoring. Using the EM algorithm of Turnbull [The empirical distribution function with arbitrarily grouped censored and truncated data, J. R. Stat. Soc. Ser. B 38 (1976), pp. 290–295] and iterative convex minorant algorithm [P. Groeneboom and J.A. Wellner, Information Bounds and Nonparametric Maximum Likelihood Estimation, Birkhäuser, Basel, 1992], we study the performance of the nonparametric maximum-likelihood estimates (NPMLEs) of the distribution function of T. Simulation results indicate that the NPMLE performs adequately for the finite sample.
Acknowledgements
The author would like to thank the associate editor and referees for their helpful and valuable comments and suggestions.