First you need to install the JAGS program. You can download the installer from https://sourceforge.net/projects/mcmc-jags/files/.
Then install rjags R package. Within R, run install.packages ("rjags").
If this doesn't work, see the troubleshooting tips below. I'll try to add more advice as particular issues come up.
| % adapted Philippe Dreuw and Thomas Deselaers | |
| % further adapted from edits by James Malcolm | |
| % finally, Shawn Lankton made some edits (www.shawnlankton.com) | |
| % and I added some quick changes - Dennis Prangle | |
| \ProvidesPackage{beamerthemeNCLDennis} | |
| %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
| \mode<presentation> | |
| %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
| # Reference class objects for gradient descent algorithms. | |
| # The "step" method take an estimated gradient as argument | |
| # and returns an increment to apply to the current parameter values. | |
| # See end of file for an example. | |
| ##Algorithm which does no adaptation | |
| noAdapt = setRefClass("noAdapt", | |
| fields = list(), | |
| methods = list( | |
| step = function(gradientEst) { |