RWLeastSqQRCalc
Class RWLeastSqQRCalc encapsulates the QR method. This method begins by decomposing the regression matrix X into the product of an orthogonal matrix Q and an upper triangular matrix R. The QR representation is then substituted into the equation in Calculation Methods for Linear Regression to obtain the solution 
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.Pros: | Good performance. Parameter values are recalculated very quickly when adding or removing predictor variables. Model selection performance is best with this calculation method. |
Cons: | Calculation fails when the regression matrix X has less than full rank. (A matrix has less than full rank if the columns of X are linearly dependent.) Results may not be accurate if X is extremely ill-conditioned. |
