coverage {divent} | R Documentation |
Sample Coverage of a Community
Description
coverage()
calculates an estimator of the sample coverage of a community
described by its abundance vector.
coverage_to_size()
estimates the sample size corresponding to the chosen
sample coverage.
Usage
coverage(x, ...)
## S3 method for class 'numeric'
coverage(
x,
estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
level = NULL,
as_numeric = FALSE,
...,
check_arguments = TRUE
)
## S3 method for class 'abundances'
coverage(
x,
estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
level = NULL,
...,
check_arguments = TRUE
)
coverage_to_size(x, ...)
## S3 method for class 'numeric'
coverage_to_size(
x,
sample_coverage,
estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
as_numeric = FALSE,
...,
check_arguments = TRUE
)
## S3 method for class 'abundances'
coverage_to_size(
x,
sample_coverage,
estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
...,
check_arguments = TRUE
)
Arguments
x |
An object. |
... |
Unused. |
estimator |
An estimator of the sample coverage.
"ZhangHuang" is the most accurate but does not allow choosing a |
level |
The level of interpolation or extrapolation, i.e. an abundance. |
as_numeric |
if |
check_arguments |
if |
sample_coverage |
The target sample coverage. |
Details
The sample coverage C
of a community is the total probability of
occurrence of the species observed in the sample.
1-C
is the probability for an individual of the whole community to
belong to a species that has not been sampled.
The historical estimator is due to Turing (Good 1953). It only relies on singletons (species observed only once). Chao's (Chao and Shen 2010) estimator uses doubletons too and Zhang-Huang's (Chao et al. 1988; Zhang and Huang 2007) uses the whole distribution.
If level
is not NULL
, the sample coverage is interpolated or extrapolated.
Interpolation by the Good estimator relies on the equality between sampling
deficit and the generalized Simpson entropy (Good 1953).
The Chao et al. (2014) estimator allows extrapolation,
reliable up a level equal to the double size of the sample.
Value
coverage()
returns a named number equal to the calculated sample coverage.
The name is that of the estimator used.
coverage_to_size()
returns a number equal to the sample size corresponding
to the chosen sample coverage.
References
Chao A, Gotelli NJ, Hsieh TC, Sander EL, Ma KH, Colwell RK, Ellison AM (2014).
“Rarefaction and Extrapolation with Hill Numbers: A Framework for Sampling and Estimation in Species Diversity Studies.”
Ecological Monographs, 84(1), 45–67.
doi:10.1890/13-0133.1.
Chao A, Lee S, Chen T (1988).
“A Generalized Good's Nonparametric Coverage Estimator.”
Chinese Journal of Mathematics, 16, 189–199.
43836340.
Chao A, Shen T (2010).
Program SPADE: Species Prediction and Diversity Estimation. Program and User's Guide..
CARE.
Good IJ (1953).
“The Population Frequency of Species and the Estimation of Population Parameters.”
Biometrika, 40(3/4), 237–264.
doi:10.1093/biomet/40.3-4.237.
Zhang Z, Huang H (2007).
“Turing's Formula Revisited.”
Journal of Quantitative Linguistics, 14(2-3), 222–241.
doi:10.1080/09296170701514189.
Examples
coverage(paracou_6_abd)
coverage_to_size(paracou_6_abd, sample_coverage = 0.9)