Description Usage Arguments Details Value Author(s) Examples

The function `std`

accepts a design matrix and returns
a standardized version of that matrix (i.e., each column will have
mean 0 and mean sum of squares equal to 1). The code has been adapted from the `ncvreg`

package (Breheny and Huang, 2011).

1 | ```
standard(X)
``` |

`X` |
A matrix (or object that can be coerced to a matrix, such as a data frame). |

This function centers and scales each column of `X`

so that

*sum(X[,j])=0*

and

*sum(X[,j]^2)=n*

for all j. This is usually not necessary to call directly, as `SSLASSO`

internally standardizes the design matrix, but inspection of the
standardized design matrix can sometimes be useful. This differs from
the base R function `scale`

in two ways: (1) `scale`

uses the sample standard deviation `sqrt(sum(x^2)/(n-1))`

, while
`std`

uses the root-mean-square, or population, standard
deviation `sqrt(mean(sum(x^2)))`

, and (2) `std`

is faster. The reason for using the population standard deviation is that `SSLASSO`

assumes that the columns of the design matrix have been scaled to have norm `sqrt(n)`

.

The standardized design matrix, with attribues "center" and "scale" corresponding to the mean and (population) standard deviation used to scale the columns.

Patrick Breheny

1 2 3 4 |

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