predict.openCR {openCR} | R Documentation |
openCR Model Predictions
Description
Evaluate an openCR capture–recapture model. That is, compute the ‘real’ parameters corresponding to the ‘beta’ parameters of a fitted model for arbitrary levels of any variables in the linear predictor.
Usage
## S3 method for class 'openCR'
predict(object, newdata = NULL, se.fit = TRUE, alpha = 0.05, savenew = FALSE, ...)
## S3 method for class 'openCRlist'
predict(object, newdata = NULL, se.fit = TRUE, alpha = 0.05, savenew = FALSE, ...)
Arguments
object |
|
newdata |
optional dataframe of values at which to evaluate model |
se.fit |
logical for whether output should include SE and confidence intervals |
alpha |
alpha level |
savenew |
logical; if TRUE then newdata is saved as an attribute |
... |
other arguments passed to |
Details
Predictions are provided for each row in ‘newdata’. The default (constructed by
makeNewData
) is to limit those rows to the first-used level of
factor predictors; to include all levels pass all.levels = TRUE
to
makeNewData
in the ... argument.
See Also
Examples
## Not run:
c1 <- openCR.fit(ovenCH, type='CJS', model=phi~session)
predict(c1)
## End(Not run)
[Package openCR version 2.2.6 Index]