n2RR: Mark-Recapture Sample Size, Robson-Regier

Description Usage Arguments Value Note Author(s) References See Also Examples

View source: R/n2.R

Description

Calculates minimum sample size for one sampling event in a Petersen mark-recapture experiment, given the sample size in the other event and an best guess at true abundance.

Usage

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n2RR(
  N,
  n1,
  conf = c(0.99, 0.95, 0.9, 0.85, 0.8, 0.75),
  acc = c(0.5, 0.25, 0.2, 0.15, 0.1, 0.05, 0.01)
)

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(0.99,0.95,0.9,0.85,0.8,0.75). Defaults to all of c(0.99,0.95,0.85,0.8,0.75).

acc

A vector of the desired levels of relative accuracy to investigate. Allowed values are any of c(0.5,0.25,0.2,0.15,0.1,0.05,0.01). Defaults to all of c(0.5,0.25,0.2,0.15,0.1,0.05,0.01).

Value

A list of minimum sample sizes. Each list element corresponds to a unique level of confidence, and is defined as a data frame with each row corresponding to a unique value of relative accuracy. Two minimum sample sizes are given: one calculated from the sample size provided for the other event, and the other calculated under n1=n2, the most efficient scenario.

Note

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

It is possible that the sample size - accuracy relationship will be better illustrated using plotn2sim.

Author(s)

Matt Tyers

References

Robson, D. S., and H. A. Regier. 1964. Sample size in Petersen mark-recapture experiments. Transactions of the American FisheriesSociety 93:215-226.

See Also

plotn2sim, plotn1n2simmatrix

Examples

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n2RR(N=1000, n1=100)

mbtyers/recapr documentation built on Sept. 13, 2021, 11:54 a.m.