Description Usage Arguments Details Value Author(s)
Use an information criterion to select a local log-linear model
1 2 |
densi |
A matrix with one row and 2^k-1 column containing cell counts or empirical cell probabilities corresponding to all the possible capture patterns. |
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 |
N |
If you multiply |
ic |
The information criterion, such as AIC, AICc, BIC, or BICpi. |
averaging |
Logical: TRUE means that we use information criterion scores to do model averaging. |
normalized |
Logical: TRUE means that beta0 will be adjusted so that the log-linear model corresponds to cell probabilities instead of expected cell counts. |
rasch |
Logical: TRUE means that the Rasch model is a candidate. |
Just like flat.IC
except that it is designed to take in a local
average instead of a full capture-recapture dataset
pred |
Estimated rate of missingness for the selected model |
form |
Formula of the selected model |
Zach Kurtz
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