ent_shannon: Shannon's Entropy of a Community

In divent: Entropy Partitioning to Measure Diversity

Shannon's Entropy of a Community

Description

Estimate the entropy \insertCiteShannon1948divent of species from abundance or probability data. Several estimators are available to deal with incomplete sampling.

Usage

ent_shannon(x, ...)

## S3 method for class 'numeric'
ent_shannon(
  x,
  estimator = c("UnveilJ", "ChaoJost", "ChaoShen", "GenCov", "Grassberger", "Marcon",
    "UnveilC", "UnveiliC", "ZhangGrabchak", "naive", "Bonachela", "Grassberger2003",
    "Holste", "Miller", "Schurmann", "ZhangHz"),
  level = NULL,
  probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
  unveiling = c("geometric", "uniform", "none"),
  richness_estimator = c("jackknife", "iChao1", "Chao1", "naive"),
  jack_alpha = 0.05,
  jack_max = 10,
  coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
  as_numeric = FALSE,
  ...,
  check_arguments = TRUE
)

## S3 method for class 'species_distribution'
ent_shannon(
  x,
  estimator = c("UnveilJ", "ChaoJost", "ChaoShen", "GenCov", "Grassberger", "Marcon",
    "UnveilC", "UnveiliC", "ZhangGrabchak", "naive", "Bonachela", "Grassberger2003",
    "Holste", "Miller", "Schurmann", "ZhangHz"),
  level = NULL,
  probability_estimator = c("Chao2015", "Chao2013", "ChaoShen", "naive"),
  unveiling = c("geometric", "uniform", "none"),
  richness_estimator = c("jackknife", "iChao1", "Chao1", "naive"),
  jack_alpha = 0.05,
  jack_max = 10,
  coverage_estimator = c("ZhangHuang", "Chao", "Turing", "Good"),
  gamma = FALSE,
  as_numeric = FALSE,
  ...,
  check_arguments = TRUE
)

Arguments

x	An object, that may be a numeric vector containing abundances or probabilities, or an object of class abundances or probabilities.
...	Unused.
estimator	An estimator of entropy.
level	the level of interpolation or extrapolation. It may be a sample size (an integer) or a sample coverage (a number between 0 and 1). If not NULL, the asymptotic estimator is ignored.
probability_estimator	a string containing one of the possible estimators of the probability distribution (see probabilities). Used only for extrapolation.
unveiling	a string containing one of the possible unveiling methods to estimate the probabilities of the unobserved species (see probabilities). Used only for extrapolation.
richness_estimator	an estimator of richness to evaluate the total number of species, see div_richness. used for interpolation and extrapolation.
jack_alpha	the risk level, 5% by default, used to optimize the jackknife order.
jack_max	the highest jackknife order allowed. Default is 10.
coverage_estimator	an estimator of sample coverage used by coverage.
as_numeric	if TRUE, a number or a numeric vector is returned rather than a tibble.
check_arguments	if TRUE, the function arguments are verified. Should be set to FALSE to save time when the arguments have been checked elsewhere.
gamma	if TRUE, \gamma diversity, i.e. diversity of the metacommunity, is computed.

Details

Bias correction requires the number of individuals.

See div_hill for non-specific estimators. Shannon-specific estimators are from \insertCiteMiller1955;textualdivent, \insertCiteGrassberger2003;textualdivent, \insertCiteSchurmann2004;textualdivent and \insertCiteZhang2012;textualdivent. More estimators can be found in the entropy package.

Entropy can be estimated at a specified level of interpolation or extrapolation, either a chosen sample size or sample coverage \insertCiteChao2014divent, rather than its asymptotic value. See accum_tsallis for details.

Value

A tibble with the site names, the estimators used and the estimated entropy.

References

\insertAllCited

Examples

# Entropy of each community
ent_shannon(paracou_6_abd)
# gamma entropy
ent_shannon(paracou_6_abd, gamma = TRUE)

# At 80% coverage
ent_shannon(paracou_6_abd, level = 0.8)

divent documentation built on April 3, 2025, 7:40 p.m.