Description Usage Arguments Value Author(s) References See Also Examples
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).
1 | GVFCMOM(counts, s, d, method, k=1, lowint=0, highint=100)
|
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 ( |
k |
Size parameter of the Negative Binomial distribution |
lowint |
Minimum value for MOM estimate (default=0) |
highint |
Maximum value for MOM estimate (default=100) |
The method of moments estimate for the transect is returned
Jon Barry: Jon.Barry@cefas.co.uk
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 |
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