cistrat {recapr} | R Documentation |
Confidence Intervals for the Stratified Estimator
Description
Calculates approximate confidence intervals(s) for the Stratified estimator, using bootstrapping, the Normal approximation, or both.
The bootstrap interval is created by resampling the data in the second sampling event, with replacement for each stratum; that is, drawing bootstrap values of m2 from a binomial distribution with probability parameter m2/n2.
Usage
cistrat(
n1,
n2,
m2,
conf = 0.95,
method = "both",
bootreps = 10000,
estimator = "Chapman",
useChapvar = FALSE
)
Arguments
n1 |
Number of individuals captured and marked in the first sample |
n2 |
Number of individuals captured in the second sample |
m2 |
Number of marked individuals recaptured in the second sample |
conf |
The confidence level of the desired intervals. Defaults to 0.95. |
method |
Which method of confidence interval to return. Allowed values
are |
bootreps |
Number of bootstrap replicates to use. Defaults to 10000. |
estimator |
The type of estimator to use. Allowed values are
|
useChapvar |
Whether to use the Chapman estimator variance instead of
the Petersen estimator variance for the normal-distribution interval, if
|
Value
A list with the abundance estimate and confidence interval bounds for the normal-distribution and/or bootstrap confidence intervals.
Note
Both the bootstrap and the normal approximation intervals make the naive assumption of independence between strata, which may not be the case. The user therefore cautioned, and is encouraged to investigate the coverage under relevant scenarios.
Author(s)
Matt Tyers
See Also
\linkstrattest, Nstrat, rstrat, vstrat, sestrat, NChapman, NPetersen, NBailey
Examples
cistrat(n1=c(100,200), n2=c(100,500), m2=c(10,10))