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Construct time series and ACF plots of the parameters phi and sigma. Include your plots and the R output with your work.

(a) Do you believe that the MCMC sample size of 3 chains, each with 2500 iterations after a burn-in of 100 iterations, is adequate? Why or why not? Is the burn-in of 100 iterations adequate? Why or why not? If you feel that either the number of iterations or the length of the burn-in period is inadequate, then rerun with a larger burn-in period and/or MCMC sample size.

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(b) How closely do the Bayes and ML estimates agree? Could you explain any possible disagreement?

(c) The model in the WinBUGS program does not assume that the time series is in its stationary distribution. In fact, the model does not even assume that there is a stationary distribution. Explain why.

(d) Modify the WinBUGS program to utilize the marginal distribution of y1, assuming that the process starts in its stationary distribution.

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