October 2015
Beginner to intermediate
168 pages
4h 11m
English
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Simulation of the posterior distribution
If one wants to find out the posterior of the model parameters, the sim( ) function of the arm package becomes handy. The following R script will simulate the posterior distribution of parameters and produce a set of histograms:
>posterior.bayes <- as.data.frame(coef(sim(fit.bayes))) >attach(posterior.bayes) >h1 <- ggplot(data = posterior.bayes,aes(x = X1)) + geom_histogram() + ggtitle("Histogram X1") >h2 <- ggplot(data = posterior.bayes,aes(x = X2)) + geom_histogram() + ggtitle("Histogram X2") >h3 <- ggplot(data = posterior.bayes,aes(x = X3)) + geom_histogram() + ggtitle("Histogram X3") >h4 <- ggplot(data = posterior.bayes,aes(x = X4)) + geom_histogram() + ggtitle("Histogram X4") >h5 <- ggplot(data = posterior.bayes,aes(x ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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