Question: 11. Suppose we have a convergent MCMC algorithm for drawing samples from p(|y) f(y|)(). We wish to locate potential outliers by computing the conditional

11. Suppose we have a convergent MCMC algorithm for drawing samples from p(θ|y) ∝ f(y|θ)π(θ). We wish to locate potential outliers by computing the conditional predictive ordinate f(yi|y(i)) given in equation

(2.29) for each i = 1,...,n. Give a computational formula we could use to obtain a simulation-consistent estimate of f(yi|y(i)). What criterion might we use to classify yi as a suspected outlier?

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