plotn2sim {recapr}

Mark-Recapture Sample Size Via Simulation

Description

Produces a plot of the simulated relative accuracy of a mark-recapture abundance estimator for various sample sizes. This may be a better representation of the sample size - accuracy relationship than that provided by n2RR.

Usage

plotn2sim(
  N,
  n1,
  conf = c(0.99, 0.95, 0.85, 0.8, 0.75),
  n2range = NULL,
  n2step = NULL,
  estimator = "Chapman",
  nsim = 10000,
  accrange = 1,
  ...
)

Arguments

N

The best guess at true abundance

n1

The size of the first (or second) sampling event

conf

A vector of the desired levels of confidence to investigate. Allowed values are any of c(0.99,0.95,0.85,0.8,0.75). Defaults to all of c(0.99,0.95,0.85,0.8,0.75).

n2range

A two-element vector describing the range of sample sizes to investigate. If the default (NULL) is accepted, an appropriate value will be chosen.

n2step

The step size between sample sizes to investigate. If the default (NULL) is accepted, an appropriate value will be chosen.

estimator

The abundance estimator to use. Allowed values are "Chapman", "Petersen", and "Bailey". Defaults to "Chapman".

nsim

The number of replicates. Defaults to 10000.

accrange

The maximum level of relative accuracy for plotting. Defaults to 1.

...

Additional plotting parameters

Note

Any Petersen-type estimator (such as this) depends on a set of assumptions:

• The population is closed; that is, that there are no births, deaths, immigration, or emigration between sampling events

• All individuals have the same probability of capture in one of the two events, or complete mixing occurs between events

• Marking in the first event does not affect probability of recapture in the second event

• Individuals do not lose marks between events

• All marks will be reported in the second event

Author(s)

Matt Tyers

See Also

n2RR, plotn1n2simmatrix

Examples

plotn2sim(N=1000, n1=100)