| RSE {secr} | 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 |
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.
See Also
Examples
RSE(secrdemo.0)