Construct a design matrix

`rmse`

is the root-mean-squared-error, `mae`

is the mean
absolute error, `qae`

is quantiles of absolute error. These can both
be interpreted on the scale of the response; `mae`

is less sensitive
to outliers. `rsquare`

is the variance of the predictions divided by
by the variance of the response.

1 2 3 4 5 6 7 |

`model` |
A model |

`data` |
The dataset |

`probs` |
Numeric vector of probabilit |

1 2 3 4 5 |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.