Previously I had asked and MattJ successfully answered the following scenario : I have X = 50 data points for 6 parameters, resulting in output vector Y of 50 data points. I have first constrained the problem so that the Y predicted values are > 0 by setting A = -X, b = 0*Y, and solved via BETA = lsqlin(X,Y,A,b) . I now want to specify multiple constraints so BETA(1)*X(1) + BETA(2)*X(2) is always > 0 , BETA(3)*X(3) + BETA(4)*X(4) > 0 , and BETA(5)*X(5) + BETA(6)*X(6) > 0 for all 50 predicted values. Can someone help me with this? Thanks.
Matt's solution was : tmp={X(:,1:2),X(:,3:4),X(:,5:6)}; A=-[X;blkdiag(tmp{:})]; b=zeros(size(A,1),1); lsqlin(X,Y,A,b)
I now need to add another constarint to the original constraints, that the ratio [BETA(1)*X(1) + BETA(2)*X(2)] / [BETA(3)*X(3) + BETA(4)*X(4)] must be between -0.7 and 0.7 Thanks.
