Truncated Poisson: Suppose observations come from Poisson(u), but only non-zero values are recorded. The likelihood is L(1) x I Data: 3, 1,2, 4, 2, 1, 3, 1, 2, 1 Prior: p() = 1 (a) Construct a...

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Extracted text: Truncated Poisson: Suppose observations come from Poisson(u), but only non-zero values are recorded. The likelihood is L(1) x I Data: 3, 1,2, 4, 2, 1, 3, 1, 2, 1 Prior: p() = 1 (a) Construct a Metropolis Hasting (M-H) algorithm. Use M-H with proposal distribution q(p) : N(0 : mean = with burn in phase 1500. Give a 95% confidence interval for p. Hps std = 2). Set Prob(acceptance) 0 if u < 0.="" number="" of="" mcmc="" draws="">