Warning: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN.

I have coding such as this:

En = length(n);         % n = number of data tottaly
Ex1= sum(x1);        % Ex1= number of Depth
Ex2= sum(x2);         % Ex2= number of Amax
Ex3= sum(x3);           % Ex3= number of Mw
Ex4= sum(x4);           % Ex4= number of Vs
Ex5= sum(x5);     % Ex5= number of Distance
x1x2= dot(x1,x2);       
x1x3= dot(x1,x3);
x1x4= dot(x1,x4);
x1x5= dot(x1,x5);
Ex1x2=sum(x1x2);
Ex1x3=sum(x1x3);
Ex1x4=sum(x1x4);
Ex1x5=sum(x1x5);
x1_2 = x1.^2;
x2_2 = x2.^2;
x3_2 = x3.^2;
x4_2 = x4.^2;
x5_2 = x5.^2;
Ex1_2 = sum(x1_2);
Ex2_2 = sum(x2_2);
Ex3_2 = sum(x3_2);
Ex4_2 = sum(x4_2);
Ex5_2 = sum(x5_2);
Ey1=sum(y1);
x1_y1=dot(x1,y1);
x2_y1=dot(x2,y1);
x3_y1=dot(x3,y1);
x4_y1=dot(x4,y1);
x5_y1=dot(x5,y1);
Ex1_y1=sum(x1_y1);                %Ex1_y = number x1 multiplyied y              
Ex2_y1=sum(x2_y1);                %Ex2_y = number of x2 multiplied by y
Ex3_y1=sum(x3_y1);
Ex4_y1=sum(x4_y1); 
Ex5_y1=sum(x5_y1);
A = [En Ex1 Ex2 Ex3 Ex4 Ex5;Ex1 Ex1_2 Ex1x2 Ex1x3 Ex1x4 Ex1x5;Ex2 Ex2_2 Ex1x2 Ex1x3 Ex1x4 Ex1x5;...
    Ex3 Ex3_2 Ex1x2 Ex1x3 Ex1x4 Ex1x5;Ex4 Ex4_2 Ex1x2 Ex1x3 Ex1x4 Ex1x5;Ex5 Ex5_2 Ex1x2 Ex1x3 Ex1x4 Ex1x5];
At = A';
G  = [Ey1;Ex1_y1;Ex2_y1;Ex3_y1;Ex4_y1;Ex5_y1];
Ai = inv(At);

I want to make an inversion task but, I got the massage like this "Warning: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN"

Is there any one can help me to slove my probelm?

Thx

[Skydriver]

The following information is contained in the ‘At’ before it was inversed:

[David Goodmanson]

Hi Akhmad,

It's better to post a small matrix like this as text rather than image, so it can be copied and used directy. Also the numbers in the first column are cut off, However, just from looking at the image,

for row 3, the values in columns 2 through 6 are identical.

for row 4, the values in columns 2 through 6 are identical.

for row 5, the values in columns 2 through 6 are identical.

for row 6, the values in columns 2 through 6 are identical.

and from this it is not hard to show that row 5 is a linear combination of rows 3 and 4, and row 6 is also a linear combination of rows 3 and 4. Either on of those is enough to make the matrix singular. I believe you need to go back to square one and look at how you are building the elements of the matrix.

Answer 1

[Skydriver]

Yes it works now, thank you David Goodmanson