Sorry, Scilab friends, I am still not fluid with vector operations.
Can someone rewrite the for loop for me into something much more efficient?
n=1000;
Z=grand(1,n,'nor',0,1);
r=0.9;
V=Z;
for i=2:n;
V(i)=r*V(i-1)+sqrt(1-r^2)*Z(i);
end;
The transformation generates an autocorrelated (here rho=0.9) normal
distribution V from an uncorrelated normal distribution Z and eventually I will
need it for very much larger n values....
Heinz
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