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secr (version 4.6.10)

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)

Value

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

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

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 \(\mbox{RSE}(\hat \theta) = \sqrt {\exp( \mbox{var}(\beta))-1}\). 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

Run this code

RSE(secrdemo.0)

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