CV: Coefficient of Variation

CVR Documentation

Coefficient of Variation


The coefficient of variation of effective sampling area predicts the bias in estimated density (Efford and Mowat 2014). These functions assist its calculation from fitted finite mixture models.


CV(x, p, na.rm = FALSE)
CVa0(object, ...)
CVa(object, sessnum = 1, ...)



vector of numeric values


vector of class probabilities


logical; if TRUE missing values are dropped from x


fitted secr finite mixture model


integer sequence number of session to analyse


other arguments passed to predict.secr (e.g., newdata)


CV computes the coefficient of variation of x. If p is provided then the distribution is assumed to be discrete, with support x and class membership probabilities p (scaled automatically to sum to 1.0).

CVa computes CV(a) where a is the effective sampling area of Borchers and Efford (2008).

CVa0 computes CV(a0) where a0 is the single-detector sampling area defined as a_0 = 2 \pi \lambda_0 \sigma^2 (Efford and Mowat 2014); a0 is a convenient surrogate for a, the effective sampling area. CV(a0) uses either the fitted MLE of a0 (if the a0 parameterization has been used), or a0 computed from the estimates of lambda0 and sigma.

CVa and CVa0 do not work for models with individual covariates.




Do not confuse the function CVa with the estimated relative standard error of the estimate of a from derived, also labelled CVa in the output. The relative standard error RSE is often labelled CV in the literature on capture–recapture, but this can cause unnecessary confusion. See also RSE.


Borchers, D. L. and Efford, M. G. (2008) Spatially explicit maximum likelihood methods for capture–recapture studies. Biometrics 64, 377–385.

Efford, M. G. and Mowat, G. (2014) Compensatory heterogeneity in capture–recapture data. Ecology 95, 1341–1348.

See Also

CVpdot, derived, details, RSE


## Not run: 

## housemouse model
morning <- subset(housemouse, occ = c(1,3,5,7,9))
msk <- make.mask((traps(morning)), nx = 32) 
morning.h2   <-, buffer = 20, model = list(g0~h2), mask = msk, 
    trace = FALSE)
CVa0(morning.h2 )

## End(Not run)

secr documentation built on Oct. 18, 2023, 1:07 a.m.