Thursday  8/14/1997  13:53:31
          Linear model with normal AR(p) disturbances

 <<< Model specification read from file pri97                                   

 <<< Data read from file fakedat                                 
 Number of variables read from file:     4
     Number of observations in file:   500
       Observations used for sample:     1 -   500

 Col     Minimum     Maximum        Mean  Stan. dev.       First        Last
   1  1.0000E+00  1.0000E+00  1.0000E+00  0.0000E+00  1.0000E+00  1.0000E+00
   2 -3.1394E+00  3.1996E+00 -4.3616E-02  9.7616E-01  1.3563E-01 -1.2951E-01
   3 -3.1440E+00  3.9421E+00  1.6236E-02  1.0562E+00  3.7056E-01 -1.7177E+00
   4 -1.3761E+01  2.0287E+01  9.6642E-01  4.6113E+00  3.0153E+00 -3.3914E+00

       First observation (t1):    1
        Last observation (t2):  500
     Number of regressors (k):    3
  Order of autoregression (p):    4
    Dependent variable column:    4
 Explanatory variable columns:    1    2    3

 Gaussian prior for covariate coefficients
 Parameter      Prior mean      Prior s.d.     Prior prec.   Initial value
         1    0.000000E+00    1.000000E+00    1.000000E+00   -1.561879E+00
         2    0.000000E+00    1.000000E+00    1.000000E+00   -6.069412E-01
         3    0.000000E+00    1.000000E+00    1.000000E+00    2.005207E-01

  Prior correlation matrix

         1      2      3
    1  1.000
    2  0.000  1.000
    3  0.000  0.000  1.000

  Normalized prior precision matrix

         1      2      3
    1  1.000
    2  0.000  1.000
    3  0.000  0.000  1.000

 Invertible Gaussian prior for AR(p) coefficients
 Parameter      Prior mean      Prior s.d.     Prior prec.   Initial value
         1    0.000000E+00    7.071068E-01    2.000000E+00    4.708759E-01
         2    0.000000E+00    7.071068E-01    2.000000E+00   -2.854451E-01
         3    0.000000E+00    7.071068E-01    2.000000E+00    1.138247E-01
         4    0.000000E+00    7.071068E-01    2.000000E+00   -6.457961E-01

 .. Means and standard deviations do not reflect invertibility constraint.
    Standard deviation of approximation of log prior kernel:    9.91626E-03
    Computation time:    0.94

 Chi-square prior for precision
 Degrees of freedom     Scale parameter     Initial draw
      1.0000000E+00       1.0000000E+00    5.8526432E-02

 Organization of simulation vector
 Covariate coefficient vector:    1
                    Precision:    4
     AR(p) coefficient vector:    5

  Markov chain Monte Carlo posterior simulation
    Parameters written in each record:         8
                           Iterations:      2000
             Skips between iterations:         0

 >>> Posterior simulation matrix written to file sim97                                   

   Iterations completed:        2000
               CPU time:     12.4489
  CPU time per iteraton:      0.0062

      1092 accepted Metropolis candidates
  Thursday  8/14/1997  13:53:49