RSE: RSE from Fitted Model
In secr: Spatially Explicit Capture-Recapture

RSE	R Documentation

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`

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.

Value

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

Note

The less explicit abbreviation CV has been used for the same quantity (sometimes expressed as a percentage). CV is used also for the relative standard deviation of a distribution.

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.