# Householder matrices

Householder matrices are square matrices of the form

$$ P = I - \beta v v^T$$

where $\beta$ is a scalar and $v$ is …

Householder matrices are square matrices of the form

$$ P = I - \beta v v^T$$

where $\beta$ is a scalar and $v$ is …

Ridge coefficients for multiple values of the regularization parameter
can be elegantly computed by updating the *thin* SVD decomposition of
the design matrix:

```
import numpy as np
from scipy import linalg
def ridge(A, b, alphas):
"""
Return coefficients for regularized least squares
min ||A x - b||^2 + alpha ||x||^2 …
```

**Update: a fast and stable norm was added to scipy.linalg in August
2011 and will be available in scipy 0.10** Last week I discussed with
Gael how we should compute the euclidean norm of a vector a using
SciPy. Two approaches suggest themselves, either calling
scipy.linalg.norm …