repar[] := ( 
(*
  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:
  theta     Transformed parameter vector
  nk        Number of elements in transformed parameter vector
*)    
nk=(npar+1)/2;   
theta=Table[par[[i]],{i,nk}];
theta[[nk]]=Log[ par[[npar]] ];
pri=pri+theta[[nk]];
)

repar0[] := ( 
(*
  This procedure is typically used to read from file information that
  may be required to interpret par in repar.  repar0 is entered once,
  before repar.
*)
)

lrange[nk_,theta_]:= (
(*
  This function indicates whether or not a parameter vector (as
  reparameterized in repar) is in the support of the prior
  Inputs:
  nk         Number of parameters in the vector
  theta      Parameter vector
  Outputs:
  lall       Set 1 if theta in Euclidean nk-space is in the
             support of the prior; otherwise set 0
  lrange     Set 1 if theta is in the support of the prior, else 0
*) 
lall=True; Return[True])