%  This routine is used to reparameterize the model, if desired.
%  (Reparameterization is often desirable to make the form of the posterior
%  closer to a multivariate normal.  See documentation in directory above.)
%  The code in this file is used for the univariate regression model;
%  editing is required for new models.
%  If parameters are not transformed, it is still necessary to copy the
%  appropriate information from par into theta and return nk.
%  Inputs 
%  pri       Logarithm of prior distribution at current parameter vector
%  par       Current record read from posterior simulation file;
%            parameter values are typically contained within this record.
%  npar      Number of elements in par
%  Outputs:
%  pri       Logarithm of prior distribution at transformed current parameter 
%            vector
%  theta     Transformed parameter vector
%  nk        Number of elements in transformed parameter vector
function [nk, theta, pri]=repar(par,npar,pri);
   nk=(npar+1)/2;
   theta=par(1:nk);
   theta(nk)=log(par(npar));
   pri=pri+theta(nk);
end;