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

## Description

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

## Usage

 1 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 θ is RSE(\hat θ) = \widehat{SE} (θ) / {\hat θ}.

For a parameter estimated using a log link with single coefficient β, the RSE is also RSE(\hat θ) = √ {\exp(\var (β))-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.

CV
 1 RSE(secrdemo.0)