title: Change point package in R using Reversible-Jump MCMC Bayesian approach
body: <p>I am looking for a way (or at least an R package) to perform Bayesian changepoint analysis with Reversible-jump MCMC approach.</p>
  
  <p>I will apply this for detecting changepoints in Typhoon time series.</p>
  
  <p>This is my reference paper: <a href="https://journals.ametsoc.org/doi/pdf/10.1175/JCLI-D-13-00744.1" rel="nofollow noreferrer">https://journals.ametsoc.org/doi/pdf/10.1175/JCLI-D-13-00744.1</a></p>
  
  <p><a href="https://i.stack.imgur.com/Gt2dg.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Gt2dg.png" alt="Figure from the above paper"></a></p>
  
  <p>I would also like to plot the <strong>posterior probability mass function</strong> for each change point.</p>
  
  <p>Here is the sample data for this:</p>
  
  <pre><code>structure(list(V1 = c(7L, 6L, 4L, 4L, 4L, 2L, 5L, 4L, 4L, 4L, 
  6L, 7L, 8L, 6L, 10L, 7L, 9L, 5L, 1L, 4L, 5L, 5L, 2L, 2L, 5L, 
  1L, 2L, 4L, 0L, 3L, 6L, 3L, 6L, 1L, 5L, 3L, 4L, 0L, 2L, 4L)), class = 
  "data.frame", row.names = c(NA, 
  -40L))
  </code></pre>
  
  <p>I found this R-package, but it is not applied for changepoint analysis:
  <a href="https://cran.r-project.org/web/packages/rjmcmc/rjmcmc.pdf" rel="nofollow noreferrer">https://cran.r-project.org/web/packages/rjmcmc/rjmcmc.pdf</a></p>
  
  <p>Can anyone point me in the right package or at least help me on how to do this in R? I'll appreciate any help.</p>