| 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]