TY - JOUR
T1 - Robust Bayesian reliability for complex systems under prior-data conflict
AU - Walter, Gero
AU - Coolen, Frank P.A.
N1 - First version submitted 2016-07-30, final revised version submitted 2017-12-09
PY - 2018/9/1
Y1 - 2018/9/1
N2 - This paper considers the quantification of system reliability in scenarios in which data, that is, failures or the absence of failures, occurring from the system's use over time, are considered surprising from the perspective of prior information. A generalized, or imprecise, Bayesian approach is presented for general system structures in which the component lifetimes have Weibull distributions with a known shape parameter. For the scale parameter, a specific set of prior distributions is assumed that enables the prior-data conflict to be reflected through the increased imprecision in the posterior reliability bounds.
AB - This paper considers the quantification of system reliability in scenarios in which data, that is, failures or the absence of failures, occurring from the system's use over time, are considered surprising from the perspective of prior information. A generalized, or imprecise, Bayesian approach is presented for general system structures in which the component lifetimes have Weibull distributions with a known shape parameter. For the scale parameter, a specific set of prior distributions is assumed that enables the prior-data conflict to be reflected through the increased imprecision in the posterior reliability bounds.
UR - http://www.scopus.com/inward/record.url?scp=85048550609&partnerID=8YFLogxK
U2 - 10.1061/AJRUA6.0000974
DO - 10.1061/AJRUA6.0000974
M3 - Article
AN - SCOPUS:85048550609
SN - 2376-7642
VL - 4
JO - ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
JF - ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
IS - 3
M1 - 04018025
ER -