# GVFCMOM: Function to calculate the method of moments visual fast count... In emon: Tools for Environmental and Ecological Survey Design

## Description

The function takes data in the form of counts per segment along a transect and uses the raw Generalised Visual Fast Count estimator (as calculated by `GVFCMOM` and its expectation (as calculated by `expected.pois` for Poisson or `expected.nb` for negative binomial) to calculate a method of moments estimator. This effectively, adjusts the biased raw GVFC estimate. The function allows counts to have either a Poisson or a Negative Binomial distribution. The method is a generalisation of the methods in Barry and Coggan (2010).

## Usage

 `1` ```GVFCMOM(counts, s, d, method, k=1, lowint=0, highint=100) ```

## Arguments

 `counts` Vector of length s that contains a count for each segment `s` Number of segments `d` Number of positive segment counts needed before counting stops `method` Whether Poisson (`"pois"`) or Negative Binomial Distribution (`"nb"`) is assumed `k` Size parameter of the Negative Binomial distribution `lowint` Minimum value for MOM estimate (default=0) `highint` Maximum value for MOM estimate (default=100)

## Value

The method of moments estimate for the transect is returned

## Author(s)

Jon Barry: [email protected]

## References

Barry J, Eggleton J, Ware S and Curtis M (2015) Generalizing Visual Fast Count Estimators for Underwater Video Surveys. Ecosphere. http://www.esajournals.org/doi/full/10.1890/ES15-00093.1

`GVFC`, `expected.pois`, `expected.nb`
 ```1 2 3 4``` ```counts = c(0, 0, 0, 0, 1, 1, 1, 2, 1) GVFCMOM(counts, s=9, d=2, method='nb', lowint=0, highint=100) GVFCMOM(counts, s=9, d=1, method='nb', lowint=0, highint=100) GVFCMOM(counts, s=9, d=1, method='pois', lowint=0, highint=100) ```