draw.hist2: Show distribution of point estimates of a set of...

In DistanceDevelopment/WiSP: Wildlife Simulation Package (wisp)

Description

Create histogram of point estimates of abundance from replicate CIR experiments.

Usage

draw.hist2(df = df, my.max = my.max)

Arguments

df	Data frame created by sim.cir.2 of repeated simulations of a 2-occasion (or 3 occasion from sim.cir.3) CIR experiment
my.max	Maximum value of point estimates to be portrayed in the histogram. This exists because the distribution of CIR point estimates of abundance tends to have a long right-tail, and unless this tail is ignored, much of the nature of the remaining distribution is lost.

Details

The function could be generalized to draw not only the distribution of the point estimate, but also the distribution of the standard error of the simulated replicates, if desired.

Value

Produces a histogram of point estimates, with a maximum specified by the user, and labeled with the arguments used to call sim.cir.2

Note

This function makes use of is.finite on the elements of the data frame prior to allowing the distribution to be plotted.

Author(s)

Eric Rexstad, RUWPA [e-mail]

References

Borchers, Buckland, and Zucchini (2002), Estimating animal abundance: closed populations. Chapter 5 http://www.ruwpa.st-and.ac.uk/estimating.abundance

See Also

sim.cir.2, sim.cir.3, make.twosex.pop

Examples

example <- make.twosex.pop(abund=200, prop.male=0.4)
example.result <- sim.cir.2(popn=example, frac.prehunt=0.2, frac.posthunt=0.4,
                  frac.harv.male=0.6, frac.harv.fem=0.02, B=200)
draw.hist2(df=example.result, my.max=1000)

DistanceDevelopment/WiSP documentation built on Sept. 18, 2020, 2:55 p.m.