secrdemo: SECR Models Fitted to Demonstration Data

Description

Demonstration data from program Density are provided both 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)

Arguments

source

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.

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 2007). 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.

Examples

Run this code

data (secrdemo)

## construct a traps object from raw trap data
## this dataset uses fmt = 'XY' (x-y coordinates included in
## both trap and capture files), but fmt = 'trapID' (capture file
## uses trap identifier) is simpler

temptrap <- read.traps(data = trapXY, detector = 'single')
plot(temptrap)

## construct a capthist object
captdata <- make.capthist(captXY, temptrap, fmt='XY')

plot(captdata, tracks = TRUE)

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