A3-package {A3} | R Documentation |

## A3 Error Metrics for Predictive Models

### Description

A package for the generation of accurate, accessible, and
adaptable error metrics for developing high quality
predictions and inferences. The name A3 (pronounced "A-Cubed")
comes from the combination of the first letters of these three
primary adjectives.

### Details

The overarching purpose of the outputs and tools in this package
are to make the accurate assessment of model errors more
accessible to a wider audience. Furthermore, a standardized set
of reporting features are provided by this package which create
consistent outputs for virtually any predictive model. This makes
it straightforward to compare, for instance, a linear regression model
to more exotic techniques such as Random forests or Support
vector machines.

The standard outputs for each model fit provided by the A3 package
include:

Average Slope: Equivalent to a linear regression coefficient.

Cross Validated `R^2`

: Robust calculation of `R^2`

(percent of squared error explained by the model compared to the null model) values adjusting for over-fitting.

p Values: Robust calculation of p-values requiring no parametric assumptions other than independence between observations (which may be violated if compensated for).

The primary functions that will be used are
`a3`

for arbitrary modeling functions and
`a3.lm`

for linear models. This package also
includes `print.A3`

and `plot.A3`

for outputting the A3 results.

### Author(s)

Scott Fortmann-Roe scottfr@berkeley.edu http://Scott.Fortmann-Roe.com

[Package

*A3* version 1.0.0

Index]