Description Usage Arguments Details Value Examples
These measures are based on the sum of squared species proportions. The
function dominance()
gives this quantity, simpson()
gives one
minus this quantity, invsimpson()
gives the reciprocal of the
quantity, and simpson_e
gives the reciprocal divided by the number
of species.
1 2 3 4 5 6 7 | simpson(x)
dominance(x)
invsimpson(x)
simpson_e(x)
|
x |
A numeric vector of species counts or proportions. |
For a vector of species counts x
, the dominance index is defined as
D = ∑_i p_i^2,
where p_i is the species proportion, p_i = x_i / N, and N is the total number of counts. This is equal to the probability of selecting two individuals from the same species, with replacement. Relation to other definitions:
Equivalent to dominance()
in skbio.diversity.alpha
.
Similar to the simpson
calculator in Mothur. They use the
unbiased estimate p_i = x_i (x_i - 1) / (N (N -1)).
Simpson's index is defined here as 1 - D, or the probability of selecting two individuals from different species, with replacement. Relation to other definitions:
Equivalent to diversity()
in vegan
with
index = "simpson"
.
Equivalent to simpson()
in skbio.diversity.alpha
.
The inverse Simpson index is 1/D. Relation to other definitions:
Equivalent to diversity()
in vegan
with
index = "invsimpson"
.
Equivalent to enspie()
in skbio.diversity.alpha
.
Similar to the invsimpson
calculator in Mothur. They use
the unbiased estimate p_i = x_i (x_i - 1) / (N (N -1)).
Simpson's evenness index is the inverse Simpson index divided by the number of species observed, 1 / (D S). Relation to other definitions:
Equivalent to simpson_e()
in skbio.diversity.alpha
.
Please be warned that the naming conventions vary between sources. For
example Wikipedia calls D the Simpson index and 1 - D the
Gini-Simpson index. We have followed the convention from vegan
, to
avoid confusion within the R
ecosystem.
The value of the dominance (0 < D ≤q 1), Simpson index, or
inverse Simpson index. The dominance is undefined if the vector sums to
zero, in which case we return NaN
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
[1] 0.3647959
[1] 0.6352041
[1] 0.6352041
[1] 2.741259
[1] 2.741259
[1] 0.6853147
[1] 0.6853147
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