NBailey: Bailey Estimator

In mbtyers/recapr: Two Event Mark-Recapture Experiment

Description

Calculates the value of the Bailey estimator for abundance in a mark-recapture experiment, with given values of sample sizes and number of recaptures. The Bailey estimator assumes a binomial probability model in the second sampling event (i.e. sampling with replacement), rather than the hypergeometric model assumed by the Petersen and Chapman estimators.

Usage

NBailey(n1, n2, m2)

Arguments

n1	Number of individuals captured and marked in the first sample. This may be a single number or vector of values.
n2	Number of individuals captured in the second sample. This may be a single number or vector of values.
m2	Number of marked individuals recaptured in the second sample. This may be a single number or vector of values.

Value

The value of the Bailey estimator, calculated as n1*(n2+1)/(m2+1)

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

References

Bailey, N.T.J. (1951). On estimating the size of mobile populations from capture-recapture data. Biometrika 38, 293-306.

Bailey, N.T.J. (1952). Improvements in the interpretation of recapture data. J. Animal Ecol. 21, 120-7.

See Also

NPetersen, NChapman, vBailey, seBailey, rBailey, pBailey, powBailey, ciBailey

Examples

NBailey(n1=100, n2=100, m2=20)

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