/*

EXGAUSS1.PRO: EXAMPLE PROGRAM TO USE THE VARHAC ESTIMATOR IN THE
GAUSS PROCEDURE VHGAUSS1.SRC


May 17, 1996



The input is a data matrix "datin" where each row is a different
observation


it1:        first observation to be used
it2:        last  observation to be used
k1:         first column to be used
k2:         last  column to be used
imax:       maximum lag order considered
ilag:       if equal to 1, then all elements enter with the same lag
            if equal to 2, then the own lag can enter with a different
            lag
            if equal to 3, then only the own lag enters
imodel:     if equal to 1, then AIC is used
            if equal to 2, then SCHWARTZ is used
            if equal to 3, then fixed lag order imax is used
imean:      if equal to 1, then the mean will be subtracted from each series
iprint:     if equal to 1, then if the covariance matrix and the chosen lag
            order will be printed on the screen

*/


/*      DATA SECTION:  As an example, we generate 5 data series.  The first
        one is an AR(2) and the other 4 are i.i.d.
*/

seed = 11211995;
datin = rndns(1100,5,seed);
dex   = datin;

datin[1,1] = 0.;
datin[2,1] = 0.;
i = 3;
do while i <= 1100;
datin[i,1] = 1.4*datin[i-1,1] - 0.5*datin[i-2,1] + dex[i,1];
i = i+ 1;
endo;
datin[1:1000,1] = datin[101:1100,1];


/*              PARAMETER SECTION                       */

it1  = 1;
it2  = 1000;
k1   = 1;
k2   = 5;
ilag   = 1;
imodel = 2;
imax   = 4;
imean  = 0;
iprint = 1;


/*        CALL THE VARHAC PROCEDURE             */


ccc = varhac(datin,it1,it2,k1,k2,imax,ilag,imodel,imean,iprint);

format /M1 /RD 10,4;

print " ";
print " VARHAC VARIANCE-COVARIANCE MATRIX";

print ccc;
print " ";

end;