how i can run least squares (LS) criterion algorithm on this data?

x1=[0.1	,	1.1	;
6.8	,	7.1	;
-3.5	,	-4.1	;
2	,	2.7	;
4.1	,	2.8	;
3.1	,	5	;
-0.8	,	-1.3	;
0.9	,	1.2	;
5	,	6.4	;
3.9	,	4	;
];   
x2=[7.1	,	4.2	;
-1.4	,	-4.3	;
4.5	,	0	;
6.3	,	1.6	;
4.2	,	1.9	;
1.4	,	-3.2	;
2.4	,	-4	;
2.5	,	-6.1	;
8.4	,	3.7	;
4.1	,	-2.2	;
]; 
%x = lsqr(A,b);

[x,flag,relres,iter,resvec,lsvec] = lsqr(x1,x2,1e-4,70);
N = length(resvec);
semilogy(0:N-1,lsvec,'--o',0:N-1,resvec,'-o')
legend("Least-squares residual","Relative residual")

I want to run least squares (LS) criterion algorithm on this data with function lsqr but i get this error please help me .if you have any solution for run least squares please tell.

error

Error using lsqr (line 88)

Right hand side must be a column vector.

Error in lsq (line 25)

[x,flag,relres,iter,resvec,lsvec] = lsqr(x1,x2,1e-4,70);

Answer 1

[Matt J]

Maybe as follows,

for i=1:size(x2,2)
[c(:,i),flag,relres,iter,resvec(:,i),lsvec(:,i)] = lsqr(x1,x2(:,i),1e-4,70);
end

[mohammad nemat]

I want to implement the least squares (LS) criterion algorithm for x1 and x2 . what is the output of this code and how it is solve the problem?

[Matt J]

what is the output of this code

See below,

x1=[0.1	,	1.1	;
6.8	,	7.1	;
-3.5	,	-4.1	;
2	,	2.7	;
4.1	,	2.8	;
3.1	,	5	;
-0.8	,	-1.3	;
0.9	,	1.2	;
5	,	6.4	;
3.9	,	4	;
];   
x2=[7.1	,	4.2	;
-1.4	,	-4.3	;
4.5	,	0	;
6.3	,	1.6	;
4.2	,	1.9	;
1.4	,	-3.2	;
2.4	,	-4	;
2.5	,	-6.1	;
8.4	,	3.7	;
4.1	,	-2.2	;
]; 

for i=1:size(x2,2)
[c(:,i),flag,relres,iter,resvec(:,i),lsvec(:,i)] = lsqr(x1,x2(:,i),1e-4,70);
end

N = length(resvec);
semilogy(0:N-1,lsvec,'--o',0:N-1,resvec,'-o')
legend("Least-squares residual x2(:,1)","Least-squares residual x2(:,2)",...
    "Relative residual x2(:,1)", "Relative residual x2(:,2)",'Location','southwest')