secr (version 4.3.0)

RSE: RSE from Fitted Model

Description

Precision of parameter estimates from an SECR model, expressed as relative standard error.

Usage

RSE(fit, parm = NULL, newdata = NULL)

Arguments

fit

secr or openCR fitted model

parm

character; names of one or more real parameters (default all)

newdata

dataframe of covariates for predict.secr

Value

Named vector of RSE, or matrix if newdata has more than one row.

Details

The relative standard error (RSE) of parameter \(\theta\) is \(RSE(\hat \theta) = \widehat{SE} (\theta) / {\hat \theta}\).

For a parameter estimated using a log link with single coefficient \(\beta\), the RSE is also \(RSE(\hat \theta) = \sqrt {\exp(\var (\beta))-1}\). This formula is used wherever applicable.

References

Efford, M. G. and Boulanger, J. 2019. Fast evaluation of study designs for spatially explicit capture--recapture. Methods in Ecology and Evolution 10, 1529--1535.

See Also

CV

Examples

# NOT RUN {
RSE(secrdemo.0)

# }