By Lee M.D., Wagenmakers E.-J.

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4, is opened, type “20000” in the field labeled updates. Typically, the number you enter in the Update Tool window will correspond to the number you entered in the end field of the Sample Monitor Tool. 13. Specify how many samples should be drawn between the recorded samples. You can, for example, specify that only every second drawn sample should be recorded. This ability to “thin” a chain is important when successive samples are not independent but autocorrelated. In our binomial example, we will record every sample that is drawn from the posterior of θ.

This gives the upper and lower values between which 95% of samples fall. Thus, it approximates the bounds on the posterior distribution that contain 95% of the posterior density. The Matlab or R code can be modified to produce credible intervals for criteria other than 95%. 21]. 1 Compare the data sets k1 = 8, n1 = 10, k2 = 7, n2 = 10 and k1 = 80, n1 = 100, k2 = 70, n2 = 100. Before you run the code, try to predict the effect that adding more trials has on the posterior distribution for δ. 2 Try the data k1 = 0, n1 = 1 and k2 = 0, n2 = 5.

Note that the Dynamic trace plot only shows 200 samples. To have the entire time series of sampled values plotted in the log file, click on history in the Sample Monitor Tool window. 24 t Fig. 5 Getting started with WinBUGS Example of an output log file. from the posterior of the unobserved variable θ. “Sampling” means drawing a set of values, so that the relative probability that any particular value will be sampled is proportional to the density of the posterior distribution at that value. 4126, .

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