Predictive sample reuse methods usually applied in low structure aparametric paradigms are shown to be useful in certain high structure situations when conjoined with a Bayesian approach. Particular attention is focused on the incomplete data situation for which two alternative sample reuse approaches are devised. The first involves differential weighting and the second a recursive sample reuse algorithm. These are applied to censored exponential survival data. The exponential approach appears to be preferable from both a computational and modelling viewpoint.
@article{urn:eudml:doc:40839,
title = {Predictive sample reuse techniques for censored data.},
journal = {Trabajos de Estad\'\i stica e Investigaci\'on Operativa},
volume = {31},
year = {1980},
pages = {433-452},
zbl = {0468.62030},
language = {en},
url = {http://dml.mathdoc.fr/item/urn:eudml:doc:40839}
}
Geisser, Seymour. Predictive sample reuse techniques for censored data.. Trabajos de Estadística e Investigación Operativa, Tome 31 (1980) pp. 433-452. http://gdmltest.u-ga.fr/item/urn:eudml:doc:40839/