capthist: Spatial Capture History Object
Description
A capthist object encapsulates all data needed by
secr.fit, except for the optional habitat mask.Details
An object of class capthist holds spatial capture histories,
detector (trap) locations, individual covariates and other data needed
for a spatially explicit capture-recapture analysis with
secr.fit.
For `single' and `multi' detectors, capthist is a matrix with one
row per animal and one column per occasion (i.e. dim(capthist) = c(nc,
noccasions)); each element is either zero (no detection) or a detector
number. For other detectors (`proximity', `count', `signal' etc.),
capthist is an array of values and dim(capthist) = c(nc,
noccasions, ntraps); values maybe binary ({--1, 0, 1}) or integer
depending on the detector type.
Deaths during the experiment are represented as negative values.
Ancillary data are retained as attributes of a capthist object as follows:
{ -- object of class traps (required)}
- session
{ -- session identifier (required)}
- covariates
{ -- dataframe of individual covariates (optional)}
- cutval
{ -- threshold of signal strength for detection (`signal' only)}
- signal
{ -- signal strength values, one per detection (`signal' only)}
- detectedXY
{ -- dataframe of coordinates for location within polygon (`polygon' only)}References
Borchers, D. L. and Efford, M. G. (2008) Spatially
explicit maximum likelihood methods for capture--recapture studies.
Biometrics 64, 377--385.
Efford, M. G., Borchers D. L. and Byrom, A. E. (2009) Density estimation
by spatially explicit capture-recapture: likelihood-based methods. In:
D. L. Thomson, E. G. Cooch and M. J. Conroy (eds) Modeling
Demographic Processes in Marked Populations. Springer, New York. Pp.
255--269.