predict.openCR: openCR Model Predictions

In openCR: Open Population Capture-Recapture

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	openCR object output from openCR.fit
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 makeNewData

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

AIC.openCR, openCR.fit

Examples

## Not run: 

c1 <- openCR.fit(ovenCH, type='CJS', model=phi~session)
predict(c1)


## End(Not run)

openCR documentation built on Sept. 25, 2022, 5:06 p.m.