generate.sample.cr: Mark-Recapture Survey Data Generation.
In dill/wisp: Wildlife Simulation Package (wisp)

Description Usage Arguments Details Value See Also Examples

This function uses the data stored in the 'pars.survey.cr´ object to create a mark-recapture sample object.

1	generate.sample.cr(pars.survey.cr, seed = NULL)

`pars.survey.cr`	object returned by the function `setpars.survey.cr` defining the mark-recapture survey parameters.
`seed`	number passed to set.seed() to initialise random number generator

A mark-recapture sample object is generated by simulating a mark-recapture survey of the population specified in generate.sample.cr. The function setpars.survey.cr must have been run to create a ‘pars.survey.cr’ object, which contains the survey specifications.

generate.sample.cr returns an object of class 'sample.cr´ which has the following elements:

`population`	object of class 'population´.
`design`	object of class 'design.cr´.
`capture`	two dimensional detection matrix that indicates which animal groups have been captured on which occasion. A `1` in row i, column j indicates that the i-th animal/group was captured on occasion j; a `1` means that it was not.
`parents`	Details of WiSP objects passed to function
`created`	Creation date and time
`seed`	equal to the parameter 'seed' passed to the function

setpars.survey.cr, summary.sample.cr plot.sample.cr

cr.reg<-generate.region(x.length=100, y.width=50)
cr.dens<-generate.density(cr.reg)
cr.poppars<-setpars.population(density.pop = cr.dens, number.groups = 100, size.method = "poisson",
                              size.min = 1, size.max = 5, size.mean = 1, exposure.method = "beta",
                              exposure.min = 2, exposure.max = 10, exposure.mean = 3,
                              exposure.shape = 0.5, type.values = c("Male","Female"),
                              type.prob = c(0.48,0.52))
cr.pop<-generate.population(cr.poppars)

cr.des<-generate.design.cr(cr.reg, n.occ = 4)
cr.survpars<-setpars.survey.cr(cr.pop, cr.des, pmin.unmarked=0.00001, pmax.unmarked=0.5, improvement=0.01)

cr.samp<-generate.sample.cr(cr.survpars)
summary(cr.samp)
plot(cr.samp)