| read.traps {secr} | R Documentation |
Construct an object of class traps with detector locations from a text file or data frame. Usage per occasion and covariates may be included.
read.traps(file = NULL, data = NULL, detector = "multi", ...)
file |
character string with name of text file |
data |
data frame of detector coordinates |
detector |
character string for detector type |
... |
other arguments to pass to read.table |
Reads a text file in which the first column is a character string identifying a detector and the next two columns are its x- and y-coordinates, separated by white space. The coordinates optionally may be followed by a string of codes '0' or '1' indicating whether the detector was operated on each occasion. A single trap-specific numeric covariate is allowed; it should be at the end of the line preceded by '/'. This format is compatible with the Density software (Efford 2007), except that all detectors are assumed to be of the same type (usage codes greater than 1 are treated as 1).
If file is missing then x-y coordinates will be taken instead
from data. This option does not allow for covariates or
usage, but they maybe added later.
detector specifies the behaviour of the detector following Efford
et al. (2009). 'single' refers to a trap that is able to catch at most
one animal at a time; 'multi' refers to a trap that may catch more than
one animal at a time. For both 'single' and 'multi' detectors a trapped
animals can appear at only one detector per occasion. Detectors of type
'proximity', such as camera traps and hair snags for DNA sampling, allow
animals to be recorded at several detectors on one occasion.
An object of class traps comprising a data frame of x- and
y-coordinates, the detector type ('single', 'multi', or 'proximity'),
and possibly other attributes.
Murray Efford murray.efford@otago.ac.nz
Efford, M. G. (2007) Density 4.1: software for spatially explicit capture–recapture. Department of Zoology, University of Otago, Dunedin, New Zealand. http://www.otago.ac.nz/density
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.
## Replace file name with a valid local name and remove '#'
# read.traps ('c:\\myfolder\\mytraps.txt', detector='proximity')
## 'mytraps.txt' should have lines like this
# 1 365 365
# 2 365 395
# 3 365 425
# etc.