### 5.52.3 QR decomposition (for TI compatibility) : QR

QR takes as argument a numeric square matrix A of size
n and two variable names, var1 and var2.

QR factorizes this matrix numerically as Q*R where
Q is an orthogonal matrix (^{t}Q*Q=I) and R is an upper triangular
matrix. QR(A,var1,var2) returns R, stores Q=A*inv(R) in var1 and R in var2.

Input :

QR([[3,5],[4,5]],Q,R)

Output the matrix R :

[[-5,-7],[0,-1]]

Then input :

Q

Output the matrix Q :

[[-0.6,-0.8],[-0.8,0.6]]