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This paper presents
a hierarchical Bayesian approach to the estimation of components’ reliability
(survival) using a Weibull model for each of them. The proposed method can be
used to estimation with general survival censored data, because the estimation
of a component’s reliability in a series (parallel) system is equivalent to the
estimation of its survival function with right- (left-) censored data. Besides
the Weibull parametric model for reliability data, independent gamma
distributions are considered at the first hierarchical level for the Weibull
parameters and independent uniform distributions over the real line as priors
for the parameters of the gammas. In order to evaluate the model, an example
and a simulation study are discussed.
The time-integrated yearly values of North Atlantic Oscillation (INAO) are found to be well correlated to the sea surface temperature. The results give the feasibility of using INAO as a good proxy for climate change and contribute to a more complete picture of the full range of variability inherent in the climate system. Moreover, the extrapolation in the future of the well identified 65-year harmonic in INAO suggests a gradual decline in global warming starting from 2005.