# olsqr¶

## Purpose¶

Computes OLS coefficients using QR decomposition.

## Format¶

b = olsqr(depvar, indepvars)
Parameters: depvar (Nx1 vector) – dependent variable indepvars (NxP matrix) – independent variables b (Px1 vector) – least squares estimates of regression of depvar on indepvars. If depvar does not have full rank, then the coefficients that cannot be estimated will be zero.

## Examples¶

// Random matrices
x = rndn(4, 4);
y = rndn(4, 1);

// Solve OLS coefficient using QR decomposition
b = olsqr(y, x);


## Remarks¶

This provides an alternative to $$y/x$$ for computing least squares coefficients.

This procedure is slower than the / operator. However, for near singular matrices it may produce better results.

The olsqr() procedure handles matrices that do not have full rank by returning zeros for the coefficients that cannot be estimated.