sestrat: Standard Error of Stratified Abundance Estimator

In mbtyers/recapr: Two Event Mark-Recapture Experiment

Description

Calculates the standard error of the stratified estimator for abundance in a mark-recapture experiment, from vectors of sample sizes and number of recaptures, with each element corresponding to each sampling stratum.

Usage

sestrat(n1, n2, m2, estimator = "Chapman")

Arguments

n1	Vector of individuals captured and marked in the first sample, from each stratum
n2	Vector of individuals captured and marked in the second sample, from each stratum
m2	Vector of marked individuals recaptured in the second sample, from each stratum
estimator	The type of estimator to use. Allowed values are "Chapman", "Petersen", and "Bailey". Default to "Chapman".

Value

The standard error of the stratified estimator

Note

It is possible that even the stratified estimate of abundance may be biased if capture probabilities differ greatly between strata. However, the bias in the stratified estimator will be much less than an estimator calculated without stratification.

This function makes the naive assumption of independence between strata. Caution is therefore recommended.

Author(s)

Matt Tyers

See Also

strattest, Nstrat, rstrat, vstrat, cistrat, NChapman, NPetersen, NBailey

Examples

sestrat(n1=c(100,200), n2=c(100,500), m2=c(10,10))

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