Influence diagnostics in exponentiated-Weibull regression models with censored data.

Ortega, Edwin M. M., Cancho, Vicente G., and Bolfarine, Heleno. "Influence diagnostics in exponentiated-Weibull regression models with censored data.." SORT 30.2 (2006): 171-192. <http://eudml.org/doc/41624>.

@article{Ortega2006,
abstract = {Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the approach is illustrated with a real data set, where it is shown that by removing the most influential observations, there is a change in the decision about which model fits the data better.},
author = {Ortega, Edwin M. M., Cancho, Vicente G., Bolfarine, Heleno},
journal = {SORT},
keywords = {Análisis de regresión; Análisis de datos censurados; Distribución exponencial; Distribución de Weibull; exponentiated-Weibull distribution; censored data; local influence; influence diagnostic; survival data},
language = {eng},
number = {2},
pages = {171-192},
title = {Influence diagnostics in exponentiated-Weibull regression models with censored data.},
url = {http://eudml.org/doc/41624},
volume = {30},
year = {2006},
}

TY - JOUR
AU - Ortega, Edwin M. M.
AU - Cancho, Vicente G.
AU - Bolfarine, Heleno
TI - Influence diagnostics in exponentiated-Weibull regression models with censored data.
JO - SORT
PY - 2006
VL - 30
IS - 2
SP - 171
EP - 192
AB - Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the approach is illustrated with a real data set, where it is shown that by removing the most influential observations, there is a change in the decision about which model fits the data better.
LA - eng
KW - Análisis de regresión; Análisis de datos censurados; Distribución exponencial; Distribución de Weibull; exponentiated-Weibull distribution; censored data; local influence; influence diagnostic; survival data
UR - http://eudml.org/doc/41624
ER -