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A Bayes linear Bayes method for estimation of correlated event rates

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Figure

Fig. 1.The relationship between the posterior mean for a process as a function of the correlation in a pool of 2 illustrating thepossibility of a local minima for situations where the posterior mean is ultimately increasing, remaining the same or decreasing.
Fig. 2.The empirical Bayes parameter estimates for the simulation example resulting from different numbers of simulatedobservations.
Table I . The differences between the posterior expectations from the full Bayes and Bayes linear Bayes methods,E(λi | n) − E2(λi; n), given the same priors under a number of different parameter values.
Fig. 4.The difference between the full Bayes and Bayes linear Bayes posterior expectations of λ1 in (c) and λ2 in (d), E(λi |n) − E2(λi; n), for different sample sizes, with ρ = 0.6.
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