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Diagnostics analysis for log‐Birnbaum–Saunders regression models with censored data
Author(s) -
Qu Hao,
Xie FengChang
Publication year - 2011
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.2010.00467.x
Subject(s) - censoring (clinical trials) , outlier , statistics , mathematics , statistic , regression analysis , homogeneity (statistics) , monte carlo method , regression , test statistic , censored regression model , econometrics , statistical hypothesis testing
This article develops influence diagnostics for log‐Birnbaum–Saunders (LBS) regression models with censored data based on case‐deletion model (CDM). The one‐step approximations of the estimates in CDM are given and case‐deletion measures are obtained. Meanwhile, it is shown that CDM is equivalent to mean shift outlier model (MSOM) in LBS regression models and an outlier test is presented based on MSOM. Furthermore, we discuss a score test for homogeneity of shape parameter in LBS regression models. Two numerical examples are given to illustrate our methodology and the properties of score test statistic are investigated through Monte Carlo simulations under different censoring percentages.