least square method.getting error using '\' or linsolve. pls help

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any kind folks who can help me out. i'm trying to implement least square method, but i'm getting some error using linsolve and '\' function. please help, and million thanks in advance!

for a =1:400
    for P=1:49
        o=(P-1)*243; 
        for r=1:35
            if r==35
                t=-2;
                pA1(1:5,1,r,P)=A(7*r-6+o:7*r+t+o,a);
                pB1(1:5,1,r,P)=B(7*r-6+o:7*r+t+o,a);
                beta(r,P)=linsolve(pA1,pB1); <--- error
% beta(r,P)=pA1\pB1;
              else
                  t=0;
                  pA(1:7+t,1,r,P)=A(7*r-6+o:7*r+t+o,a);
                  pB(1:7+t,1,r,P)=B(7*r-6+o:7*r+t+o,a);
                  beta(r,P)=linsolve(pA,pB);; <---- error
% beta(r,P)=pA\pB;
              end
          end
      end

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Stephen23 2015-1-23

Can you please tell us what the complete error message is. We cannot read minds, and we also cannot read what is on your computer screen.

seprienna 2015-1-23

在 MATLAB Online 中打开

many thanks for willing to help me out.

The complete message for linsolve is as follows:

   Error using linsolve
    First and second arguments must be 2D.
    Error in modifiedregression (line 34)
                    beta(r,P)=linsolve(pA,pB);

whereas for \ is as follows:

Error using  \ 
Inputs must be 2-D, or at least one input must be scalar.
To compute elementwise LDIVIDE, use LDIVIDE (.\) instead.
Error in modifiedregression (line 36)
 beta(r,P)=pA\pB;

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Answer 1

Matt J 2015-1-23

编辑：Matt J 2015-1-23

0 个投票

Your pA1 and pB1 are 4D arrays. However linsolve(A,B) expects A and B to be 2D matrices, and similarly for '\'.

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seprienna 2015-1-23

i'm still trying to figure out a method to overcome the arrays to matrices. any tips from you? your kind reply is greatly appreciated

Matt J 2015-1-23

Nope, no tips. We have no way of understanding what your code is trying to do unless you explain it to us.

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