Estimate the entropy of species from abundance or probability data and a similarity matrix between species. Several estimators are available to deal with incomplete sampling. Bias correction requires the number of individuals.
ent_similarity(x, similarities, q = 1, ...)
# S3 method for class 'numeric'
ent_similarity(
x,
similarities = diag(length(x)),
q = 1,
estimator = c("UnveilJ", "Max", "ChaoShen", "MarconZhang", "UnveilC", "UnveiliC",
"naive"),
probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
unveiling = c("geometric", "uniform", "none"),
jack_alpha = 0.05,
jack_max = 10,
coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
sample_coverage = NULL,
as_numeric = FALSE,
...,
check_arguments = TRUE
)
# S3 method for class 'species_distribution'
ent_similarity(
x,
similarities = diag(sum(!colnames(x) %in% non_species_columns)),
q = 1,
estimator = c("UnveilJ", "Max", "ChaoShen", "MarconZhang", "UnveilC", "UnveiliC",
"naive"),
probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
unveiling = c("geometric", "uniform", "none"),
jack_alpha = 0.05,
jack_max = 10,
coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
gamma = FALSE,
...,
check_arguments = TRUE
)
An object, that may be a numeric vector containing abundances or probabilities,
or an object of class abundances or probabilities.
If it is a numeric vector, then its length must equal the dimensions of the
similarities
matrix: species are assumed to be in the same order.
A similarity matrix, that can be obtained by fun_similarity. Its default value is the identity matrix.
The order of diversity.
Unused.
An estimator of entropy.
A string containing one of the possible estimators of the probability distribution (see probabilities). Used only for extrapolation.
A string containing one of the possible unveiling methods to estimate the probabilities of the unobserved species (see probabilities). Used only for extrapolation.
The risk level, 5% by default, used to optimize the jackknife order.
The highest jackknife order allowed. Default is 10.
An estimator of sample coverage used by coverage.
The sample coverage of x
calculated elsewhere.
Used to calculate the gamma diversity of meta-communities, see details.
If TRUE
, a number or a numeric vector is returned rather than a tibble.
If TRUE
, the function arguments are verified.
Should be set to FALSE
to save time when the arguments have been checked elsewhere.
If TRUE
, \(\gamma\) diversity, i.e. diversity of the metacommunity, is computed.
A tibble with the site names, the estimators used and the estimated entropy.
All species of the species_distribution
must be found in the matrix of
similarities
if it is named.
If it is not or if x
is numeric, its size must equal the number of species.
Then, the order of species is assumed to be the same as that of the
species_distribution
or its numeric equivalent.
Similarity-Based entropy can't be interpolated of extrapolated as of the state of the art.
# Similarity matrix
Z <- fun_similarity(paracou_6_fundist)
# Diversity of each community
ent_similarity(paracou_6_abd, similarities = Z, q = 2)
#> # A tibble: 4 × 5
#> site weight estimator order entropy
#> <chr> <dbl> <chr> <dbl> <dbl>
#> 1 subplot_1 1.56 UnveilJ 2 0.234
#> 2 subplot_2 1.56 UnveilJ 2 0.248
#> 3 subplot_3 1.56 UnveilJ 2 0.245
#> 4 subplot_4 1.56 UnveilJ 2 0.228
# gamma diversity
ent_similarity(paracou_6_abd, similarities = Z, q = 2, gamma = TRUE)
#> # A tibble: 1 × 4
#> site estimator order entropy
#> <chr> <chr> <dbl> <dbl>
#> 1 Metacommunity UnveilJ 2 0.237