### 2.48.3 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]]`