Description Usage Arguments Value Author(s)

Given several sets of log-linear terms, compute the IC corresponding to each model.

1 | ```
ic.all(models, ddat, ic, normalized = normalized)
``` |

`models` |
A list of character vectors, with each vector containing
column names from the associated log-linear design matrix.
For example, see the output of |

`ddat` |
The log-linear design matrix. |

`ic` |
The information criterion, such as AIC, AICc, BIC, or BICpi. |

`normalized` |
Logical: TRUE means that beta0 will be adjusted so that the log-linear model corresponds to cell probabilities instead of expected cell counts. |

A matrix with as many rows as there are entries in `models`

.
The columns contain the point estimates of the population size, the
information criterion scores, and the information criterion weights for all
the models, which sum to one

Zach Kurtz

lllcrc documentation built on May 30, 2017, 7:10 a.m.

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