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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

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.

See Also

Examples

RSE(secrdemo.0)

secr

Spatially Explicit Capture-Recapture

v4.4.1
GPL (>= 2)
Authors
Murray Efford
Initial release
2021-05-01

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