TY - JOUR
T1 - Birnbaum-Saunders mixed models for censored reliability data analysis
AU - Villegas, Cristian
AU - Paula, Gilberto A.
AU - Leiva, Víctor
N1 - Funding Information:
Manuscript received February 28, 2010; revised February 11, 2011 and May 01, 2011; accepted May 19, 2011. Date of publication October 17, 2011; date of current version December 02, 2011. This research was partially supported by CNPq and FAPESP grants from Brazil and by FONDECYT 1080326 grant from Chile. Associate Editor: L. Walls. C. Villegas is with the Universidade ister_villegas@yahoo.com.ar).
PY - 2011/12
Y1 - 2011/12
N2 - The Birnbaum-Saunders distribution is a useful model for describing fatigue and reliability data. This model allows us to relate the total time until the failure to some type of cumulative damage. The majority of the models based on the Birnbaum-Saunders distribution have assumed fixed-effects, and a few have been investigated for correlated data. In this work, we introduce Birnbaum-Saunders mixed models for censored data. Specifically, we estimate their parameters by means of the Gauss-Hermite quadrature approximation, carry out a residual analysis for these models, and conduct an application using real censored reliability data. This application illustrates the utility of a Birnbaum-Saunders random intercept model.
AB - The Birnbaum-Saunders distribution is a useful model for describing fatigue and reliability data. This model allows us to relate the total time until the failure to some type of cumulative damage. The majority of the models based on the Birnbaum-Saunders distribution have assumed fixed-effects, and a few have been investigated for correlated data. In this work, we introduce Birnbaum-Saunders mixed models for censored data. Specifically, we estimate their parameters by means of the Gauss-Hermite quadrature approximation, carry out a residual analysis for these models, and conduct an application using real censored reliability data. This application illustrates the utility of a Birnbaum-Saunders random intercept model.
KW - Gauss-Hermite quadrature
KW - log-linear models
KW - random intercept models
KW - residual analysis
KW - sinh-normal distribution
UR - http://www.scopus.com/inward/record.url?scp=82455210751&partnerID=8YFLogxK
U2 - 10.1109/TR.2011.2170251
DO - 10.1109/TR.2011.2170251
M3 - Article
AN - SCOPUS:82455210751
VL - 60
SP - 748
EP - 758
JO - IEEE Transactions on Reliability
JF - IEEE Transactions on Reliability
SN - 0018-9529
IS - 4
M1 - 6045312
ER -