How to generate a random data vector that follows a constraint
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Saifullah Khalid
le 29 Sep 2019
Commenté : Saifullah Khalid
le 30 Sep 2019
I want to generate random data vector where that follows this constrainst. where and is a constant. I would appreciate any help.
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Bruno Luong
le 29 Sep 2019
Modifié(e) : Bruno Luong
le 29 Sep 2019
This will generate uniform distribution (within to polytope)
N = 10;
Etotal = 0;
E = -log(rand(N+1,1));
E = E(1:N,:)./sum(E,1);
2 commentaires
Bruno Luong
le 29 Sep 2019
Modifié(e) : Bruno Luong
le 29 Sep 2019
Here is a comparison of distribution with the two other methods proposed below to show the issue of non-uniformity if one doesn't pay attention
N = 2;
Etotal = 1;
p = 3e3;
Ebias = rand(1,p) .* randfixedsum(N,p,Etotal,0,Etotal);
E = rand(1,p).^(1/N)*Etotal .* randfixedsum(N,p,1,0,1);
E2 = -log(rand(N+1,p)); E2 = E2(1:N,:)./sum(E2,1);
subplot(2,2,1)
plot(Ebias(1,:),Ebias(2,:),'.');
title('rand * randfixedsum')
axis equal
subplot(2,2,2)
plot(E(1,:),E(2,:),'.');
axis equal
title('sqrt(rand) * randfixedsum')
subplot(2,2,3)
plot(E2(1,:),E2(2,:),'.');
axis equal
title('exponential method')
Plus de réponses (1)
Walter Roberson
le 29 Sep 2019
Look in the File Exchange for Roger's randfixedsum(). Generate a vector with fixed sum . Multiply all of the elements by rand() to implement the <= part. (Though you might want to worry about the difficulty that rand() is never exactly 1, so if you generate a sum exactly equal to and multiply by rand() then the result can never exactly total
3 commentaires
Walter Roberson
le 29 Sep 2019
I was thinking of
rand() * randfixedsum(N,1,Etotal,0,Etotal)
but your comment might still apply.
Bruno Luong
le 29 Sep 2019
Modifié(e) : Bruno Luong
le 29 Sep 2019
Both give the same non-uniform pdf
The "correct" one is
E = rand()^(1/N)*Etotal * randfixedsum(N,1,1,0,1);
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