Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

secrdemo

SECR Models Fitted to Demonstration Data


Description

Demonstration data from program Density are provided as text files in the ‘extdata’ folder, as raw dataframes (trapXY, captXY), and as a combined capthist object (captdata) ready for input to secr.fit.

The fitted models are objects of class secr formed by

secrdemo.0 <- secr.fit (captdata)

secrdemo.b <- secr.fit (captdata, model = list(g0 = ~b))

secrdemo.CL <- secr.fit (captdata, CL = TRUE)

Usage

data(secrdemo)

Details

The raw data are 235 fictional captures of 76 animals over 5 occasions in 100 single-catch traps 30 metres apart on a square grid with origin at (365,365).

Dataframe trapXY contains the data from the Density input file ‘trap.txt’, and captXY contains the data from ‘capt.txt’ (Efford 2012).

The fitted models use a halfnormal detection function and the likelihood for multi-catch traps (expect estimates of g0 to be biased because of trap saturation Efford et al. 2009). The first is a null model (i.e. parameters constant) and the second fits a learned trap response.

Object Description
captXY data.frame of capture data
trapXY data.frame of trap locations
captdata capthist object
secrdemo.0 fitted secr model -- null
secrdemo.b fitted secr model -- g0 trap response
secrdemo.CL fitted secr model -- null, conditional likelihood

References

Efford, M. G. (2012) DENSITY 5.0: software for spatially explicit capture–recapture. Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand. https://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.

See Also

Examples

## Not run: 

## navigate to folder with raw data files
olddir <- setwd (system.file("extdata", package="secr"))

## construct capthist object from raw data
captdata  <- read.capthist ("capt.txt", "trap.txt", fmt = "XY", detector = "single")

## generate demonstration fits
secrdemo.0 <- secr.fit (captdata)
secrdemo.CL <- secr.fit (captdata, CL = TRUE)
secrdemo.b <- secr.fit (captdata, model = list(g0 ~ b))

## restore previous setting
setwd(olddir)

## End(Not run)

## display the null model fit, using the print method for secr
secrdemo.0

## compare fit of models
AIC(secrdemo.0, secrdemo.b)

## display estimates for the two models (single session)
collate(secrdemo.0, secrdemo.b)[1,,,]

secr

Spatially Explicit Capture-Recapture

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

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.