# seBailey: Standard Error of the Bailey Estimator In mbtyers/recapr: Estimating, Testing, and Simulating Abundance in a Mark-Recapture

## Description

Calculates the standard error of the Bailey estimator in a mark-recapture experiment, with given values of sample sizes and number of recaptures.

## Usage

 `1` ```seBailey(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 estimate variance of the Bailey estimator, calculated as sqrt((n1^2)*(n2+1)*(n2-m2)/(m2+1)/(m2+1)/(m2+2))

## 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

Matt Tyers

## See Also

NBailey, vBailey, rBailey, pBailey, powBailey, ciBailey

## Examples

 `1` ```seBailey(n1=100, n2=100, m2=20) ```

mbtyers/recapr documentation built on May 22, 2017, 1:06 a.m.