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Generalized Simpson's Diversity

Source: R/div_gen_simpson.R
div_gen_simpson.Rd

Estimate the diversity sensu stricto, i.e. the effective number of species (Grabchak et al. 2017) from abundance or probability data.

Usage

div_gen_simpson(x, k = 1, ...)

# S3 method for class 'numeric'
div_gen_simpson(
  x,
  k = 1,
  estimator = c("Zhang", "naive"),
  as_numeric = FALSE,
  ...,
  check_arguments = TRUE
)

# S3 method for class 'species_distribution'
div_gen_simpson(
  x,
  k = 1,
  estimator = c("Zhang", "naive"),
  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.

k

the order of Hurlbert's diversity.

...

Unused.

estimator

An estimator of asymptotic diversity.

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.

Value

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

Details

Bias correction requires the number of individuals.

Estimation techniques are from Zhang and Grabchak (2016) . It is limited to orders \(k\) less than or equal to the number of individuals in the community.

Generalized Simpson's diversity cannot be estimated at a specified level of interpolation or extrapolation, and diversity partitioning is not available.

References

Grabchak M, Marcon E, Lang G, Zhang Z (2017). “The Generalized Simpson's Entropy Is a Measure of Biodiversity.” Plos One, 12(3), e0173305. doi:10.1371/journal.pone.0173305 .

Zhang Z, Grabchak M (2016). “Entropic Representation and Estimation of Diversity Indices.” Journal of Nonparametric Statistics, 28(3), 563–575. doi:10.1080/10485252.2016.1190357 .

See also

ent_gen_simpson

Examples

# Diversity of each community
div_gen_simpson(paracou_6_abd, k = 50)
#> # A tibble: 4 × 5
#>   site      weight estimator order diversity
#>   <chr>      <dbl> <chr>     <dbl>     <dbl>
#> 1 subplot_1   1.56 Zhang        50      1.01
#> 2 subplot_2   1.56 Zhang        50      1.02
#> 3 subplot_3   1.56 Zhang        50      1.01
#> 4 subplot_4   1.56 Zhang        50      1.01