point.sim.pl: Plot Sampling Method : Simulation

In dill/wisp: Wildlife Simulation Package (wisp)

Description

This function simulates surveys and estimates abundance and related parameters for each simulated survey.

Usage

        point.sim.pl(pop.spec, design.spec, B = 99, HT = FALSE, seed=NULL, show=FALSE, plot=FALSE)

Arguments

pop.spec	population specification; either an object of class 'population' or 'pars.population'
design.spec	design specification; either an object of class 'design.pl' or 'pars.design.no'
B	number of simulations required
HT	argument in point.est.pl - HT: if FALSE, the abundance estimate produced is the MLE, if TRUE it is the Horvitz-Thompson estimate.
seed	Equal to the argument 'seed' passed to the function
show	if TRUE displays the position of plots and the observations 'seen', for each simulated survey as it is run
plot	if TRUE a histogram of the group abundance point estimates obtained from each sample object is produced with true group abundance and the mean of the simulated abundance estimates displayed on the plot

Details

This function simulates surveys by simulating from the state model if pop.spec is of class 'pars.population' (using pop.spec to generate new populations on each simulation ) and if design.spec is of class 'pars.design.dp' from the design (using design.spec to generate new design realisations on each simulation.)

Value

An object of class point.sim.ce with the following elements:

A results matrix, each row of which contains the following values:
Nhat.grp	MLE of group abundance
Nhat.ind	MLE of individual abundance (= Nhat.grp * Es)
Es	Estimate of mean group size (simple mean of observed group sizes)
true	The true (simulated) values of group abundance, animal abundance and mean group size
HT	Equal to the argument 'model.sel' passed to the function
random.pop	TRUE if population is randomised
random.design	TRUE is design is randomised
parents	Details of WiSP objects passed to function
created	Creation date and time
seed	Equal to the argument 'seed' passed to the function

See Also

setpars.population, setpars.design.pl point.est.pl, set.seed

Examples

pl.reg <- generate.region(x.length = 100, y.width = 50)
pl.dens <- generate.density(pl.reg)
pl.poppars<-setpars.population(density.pop=pl.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 = 6,
                               exposure.shape = 1)
pl.pop <- generate.population(pl.poppars, seed=456)
pl.despars<-setpars.design.pl(pl.reg, n.interval.x = 10, n.interval.y = 20,
                              method = "random", area.covered = 0.2)
pl.des <- generate.design.pl(pl.despars, seed=789)

pl.samp<-generate.sample.pl(pl.pop, pl.des, seed=101112)
plot(pl.samp, whole.population=TRUE)

# To simulate with fixed population and random design realizations:
pl.sim<-point.sim.pl(pop.spec=pl.pop, design.spec=pl.despars, B=99, show=TRUE)
summary(pl.sim)
plot(pl.sim)
plot(pl.sim, type="hist")
plot(pl.sim, type="box")

# To simulate with fixed design realization and random animal locations:
pl.sim<-point.sim.pl(pop.spec=pl.poppars, design.spec=pl.des, B=99,)
summary(pl.sim)
plot(pl.sim)

# To simulate with random population and random design realizations:
pl.sim<-point.sim.pl(pop.spec=pl.poppars, design.spec=pl.despars, B=99)
summary(pl.sim)
plot(pl.sim)

dill/wisp documentation built on May 15, 2019, 8:31 a.m.