/*
** Autocorrelated Regression Models: 
** Nonlinear Maximum Likelikood Estimation
** AR(1), MA(1), ARMA(1,1)
** Greene [1999], Chap. 13
*/
use gpe2;

n=21;
load data[n,5]=c:\course07\xmu\usinv.txt;
rinv=data[2:n,3]./data[2:n,4];  @ real investment @
rgnp=data[2:n,2]./data[2:n,4];  @ real GNP @
rate=data[2:n,5]-               @ real interest rate @
     100*(data[2:n,4]-lagn(data[2:n,4],1))./lagn(data[2:n,4],1);
data=packr(rinv~rate~rgnp);
data=data~ones(rows(data),1);
/*
data matrix is arranged with the dependent variable in the first column,
followed by colums of independent variables including constant    
*/
@ OLS estimates as Table 13.2 of Greene [1999] @
b=data[.,1]/data[.,2:4];
/*
test for model specification
*/
/*
call reset;
_rplot=2;
_rtest={1,1,5,5};
_acf=10;
_acf2=10;
call estimate(data[.,1],data[.,2:3]);
*/

_nlopt=1;
_method=3;
_iter=200;
_print=0;

_arma={1,0};
call estimate(data[.,1],data[.,2:3]);

_arma={0,1};
call estimate(data[.,1],data[.,2:3]);

_arma={1,1,0.5,-0.5};
call estimate(data[.,1],data[.,2:3]);

end;