| similarity | R Documentation |
Similarity
similarity(object, ...)
## S4 method for signature 'matrix'
similarity(
object,
method = c("brainerd", "bray", "jaccard", "morisita", "sorenson")
)
## S4 method for signature 'data.frame'
similarity(
object,
method = c("brainerd", "bray", "jaccard", "morisita", "sorenson")
)
object |
A |
... |
Currently not used. |
method |
A |
\beta-diversity can be measured by addressing similarity
between pairs of samples/cases.
bray, jaccard, morisita and sorenson indices provide a scale of
similarity from 0-1 where 1 is perfect similarity and
0 is no similarity.
brainerd is scaled between 0 and 200.
brainerdBrainerd-Robinson quantitative index.
brayBray-Curtis similarity (Sorenson quantitative index).
jaccardJaccard qualitative index.
morisitaMorisita-Horn quantitative index.
sorensonDice-Sorenson index (Sorenson qualitative index).
For jaccard and sorenson, data are standardized on a presence/absence
scale (0/1) beforehand.
A stats::dist object.
N. Frerebeau
Magurran, A. E. (1988). Ecological Diversity and its Measurement. Princeton, NJ: Princeton University Press. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/978-94-015-7358-0")}.
index_binomial(), index_brainerd(), index_bray(),
index_jaccard(), index_morisita(), index_sorenson()
Other diversity measures:
heterogeneity(),
occurrence(),
plot_diversity,
plot_rarefaction,
profiles(),
rarefaction(),
richness(),
she(),
simulate(),
turnover()
## Data from Huntley 2004, 2008
data("pueblo")
## Brainerd-Robinson measure
(C <- similarity(pueblo, "brainerd"))
plot_spot(C)
## Data from Magurran 1988, p. 166
data("aves")
## Jaccard measure (presence/absence data)
similarity(aves, "jaccard") # 0.46
# Bray and Curtis modified version of the Sorenson index (count data)
(sim <- similarity(aves, "bray")) # 0.44
# Bray and Curtis dissimilarity
1 - sim
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