Abstract
Necessary and sufficient conditions for weak and strong convergence are derived for the weighted version of a general process under random censoring. To be more explicit, this means that for this process complete analogues are obtained of the Chibisov-O'Reilly theorem, the Lai-Wellner Glivenko-Cantelli theorem, and the James law of the iterated logarithm for the empirical process. The process contains as special cases the so-called basic martingale, the empirical cumulative hazard process, and the product-limit process. As a tool we derive a Kiefer-process-type approximation of our process, which may be of independent interest.
Original language | English |
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Pages (from-to) | 77-89 |
Number of pages | 13 |
Journal | Canadian Journal of Statistics / La Revue Canadienne de Statistique |
Volume | 20 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1992 |