Description Usage Arguments Value Author(s) References See Also Examples

This function uses the leaps package to find the best models of each size, and scores each according to AIC, corrected AIC, BIC, EIC and CVIC.

1 |

`y` |
outcome vector |

`X` |
model matrix. This should not include an intercept column; such a column is added by the function. |

`nboot` |
number of bootstrap samples or subsamples. |

`nfold` |
number of folds cross validation conduct. |

`names` |
vector of names for the columns of |

A matrix. The first `ncol(X)`

columns, essentially the `which`

component of an object outputted by `leaps`

, identify which predictors are in each of the best models. The remaining columns provide the AIC, corrected AIC, BIC, EIC, and CVIC for each model. The matrix has an
attribute "`npred`

" giving the number of candidate predictors, i.e.,
`ncol(X)`

.

Philip Reiss phil.reiss@nyumc.org and Lei Huang huangracer@gmail.com

Lumley, T., using Fortran code by A. Miller (2009). leaps: regression subset selection. R package version 2.9. http://CRAN.R-project.org/package=leaps

Reiss, P. T., Huang, L., Cavanaugh, J. E., and Roy, A. K. (2012). Resampling-based information criteria for adaptive linear model selection.
*Annals of the Institute of Statistical Mathematics*, to appear. Available at http://works.bepress.com/phil_reiss/17

`bestmods`

; `leaps`

(in the package of the same name)

1 | ```
## see example for bestmods
``` |

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