...
for(tt=2;tt<=tot_day;tt++) {
h[tt]=beta_0 + beta_1*h[tt-1] + beta_2*h[tt-1] ...
for (i=0; i<200 ; i++) {
double temp=l(y[tt]/h[tt],y[tt-1]) ;
temp +=exp(-lambda+i*log(lambda)-log_i+log(pgauss...
}
}
lli += log(l(y[tt]/h[tt], y[tt-1]));h[tt] is my variance temp is my normal density function - the sum is after i l is conditional probability density function lli is log likelihood function - the sum is after tt ( y[tt])
