anchor.diff:  the sum of the absolute vector elements (and is identical to the L1-norm).
   
   Matrices provide `RowSums` and `ColumnSums` functions that return the sum of each
  -row or column vector.
  +row or column vector, and `RowAbsoluteSums` and `ColumnAbsoluteSums` for the
  +sums of the absolute elements.
   
   
   Condition Number
  
positive.code: It is the orthogonal complement to the row space of the matrix.
  
  The nullity of a matrix is the dimension of its null space.
  An othonormal basis of the null space can be computed with the kernel method.
  
      [lang=csharp]
      // with the same m as above
  
negative.code: For sparse data consider to use the iterative solvers instead if appropriate,
  or convert to dense if small enough.
  
  * **Cholesky**: Cholesky decomposition of symmetric positive definite matrices
  * **LU**: LU decomposition of square matrices
  * **QR(method)**: QR by Householder transformation.
    Thin by default (Q: mxn, R: nxn) but can optionally be computed fully (Q: mxm, R: mxn).
  