Predictive sample reuse techniques for censored data.
Trabajos de Estadística e Investigación Operativa (1980)
- Volume: 31, Issue: 1, page 433-452
- ISSN: 0041-0241
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topGeisser, Seymour. "Predictive sample reuse techniques for censored data.." Trabajos de Estadística e Investigación Operativa 31.1 (1980): 433-452. <http://eudml.org/doc/40839>.
@article{Geisser1980,
abstract = {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.},
author = {Geisser, Seymour},
journal = {Trabajos de Estadística e Investigación Operativa},
keywords = {Predicción estadística; Diseño muestral; Análisis bayesiano; Análisis de datos censurados; predictive sample reuse methods; censored exponential survival data; discrepancy measure; maximum likelihood; method of moments},
language = {eng},
number = {1},
pages = {433-452},
title = {Predictive sample reuse techniques for censored data.},
url = {http://eudml.org/doc/40839},
volume = {31},
year = {1980},
}
TY - JOUR
AU - Geisser, Seymour
TI - Predictive sample reuse techniques for censored data.
JO - Trabajos de Estadística e Investigación Operativa
PY - 1980
VL - 31
IS - 1
SP - 433
EP - 452
AB - 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.
LA - eng
KW - Predicción estadística; Diseño muestral; Análisis bayesiano; Análisis de datos censurados; predictive sample reuse methods; censored exponential survival data; discrepancy measure; maximum likelihood; method of moments
UR - http://eudml.org/doc/40839
ER -
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