tag:blogger.com,1999:blog-3240271627873788873.post4457973812893892728..comments2024-03-26T06:46:11.752-04:00Comments on Doing Bayesian Data Analysis: Metropolis Algorithm: Discrete Position ProbabilitiesJohn K. Kruschkehttp://www.blogger.com/profile/17323153789716653784noreply@blogger.comBlogger2125tag:blogger.com,1999:blog-3240271627873788873.post-22027958461193620682012-08-07T17:07:01.846-04:002012-08-07T17:07:01.846-04:00Pure awesomeness!! Thank you very, very much!!Pure awesomeness!! Thank you very, very much!!echttps://www.blogger.com/profile/05050149920052393997noreply@blogger.comtag:blogger.com,1999:blog-3240271627873788873.post-10472786021946515192012-08-07T15:30:27.682-04:002012-08-07T15:30:27.682-04:00P.S. The graphs in this example would have been be...P.S. The graphs in this example would have been better if their y-axes started at zero, as in Figure 7.2 of the book. You can do that by adding an argument to the plot() commands: ylim=c(0,max(positionVec)) and ylim=c(0,max(pTarget))John K. Kruschkehttps://www.blogger.com/profile/17323153789716653784noreply@blogger.com