Editing Software Plugins and Codes (section)

===Running a model in R===

This is pretty much just following the example from the runjags documentation for autorun.jags .

We determine the number of data points and stick our data in an R list format:

 n <- length(dataframe$cage)
 jagsdata <- list (age=dataframe$cage, y=dataframe$fnbmd10, n=n)

We read in the model as a test string.  This worked for me, but I suspect that there is an easier way.

 modelraw <- readBin("findcp.model", raw(), 9000)
 model <- rawToChar(modelraw)

The last argument to readBin is the number of bytes to read.  Just make sure that this is bigger than the file size and you will get the whole file.

Now we run the model:

 results <- autorun.jags(model=model, monitor=c("b.cutoff", "b.slope", "b.intercept"), data=jagsdata)

You can analyze the traceplots of the results to assess convergence:

 results$trace

To get a summary of the monitored variables:

 results$summary

This will look something like this:

<source lang=text>
Iterations = 1:21741
Thinning interval = 2 
Number of chains = 2 
Sample size per chain = 10871 

1. Empirical mean and standard deviation for each variable,
   plus standard error of the mean:

                 Mean        SD  Naive SE Time-series SE
b.cutoff    43.152034 5.9029519 4.003e-02      1.799e-01
b.slope     -0.003935 0.0006817 4.624e-06      1.866e-05
b.intercept  0.832309 0.0102962 6.983e-05      2.305e-04

2. Quantiles for each variable:

                 2.5%       25%       50%       75%     97.5%
b.cutoff    31.641838 39.016150 42.733250 47.586850 53.975075
b.slope     -0.005512 -0.004329 -0.003827 -0.003447 -0.002851
b.intercept  0.813198  0.825117  0.832013  0.839125  0.853183
</source>