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
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