similarity {tabula}

Similarity

Description

Similarity

Usage

similarity(object, ...)

## S4 method for signature 'matrix'
similarity(
  object,
  method = c("brainerd", "bray", "jaccard", "morisita", "sorenson", "binomial")
)

## S4 method for signature 'data.frame'
similarity(
  object,
  method = c("brainerd", "bray", "jaccard", "morisita", "sorenson", "binomial")
)

Arguments

object

A m \times p numeric matrix or data.frame of count data (absolute frequencies giving the number of individuals for each category, i.e. a contingency table). A data.frame will be coerced to a numeric matrix via data.matrix().

...

Currently not used.

method

A character string specifying the method to be used (see details). Any unambiguous substring can be given.

Details

\beta-diversity can be measured by addressing similarity between pairs of samples/cases (Brainerd-Robinson, Jaccard, Morisita-Horn and Sorenson indices). Similarity between pairs of taxa/types can be measured by assessing the degree of co-occurrence (binomial co-occurrence).

Jaccard, Morisita-Horn and Sorenson indices provide a scale of similarity from 0-1 where 1 is perfect similarity and 0 is no similarity. The Brainerd-Robinson index is scaled between 0 and 200. The Binomial co-occurrence assessment approximates a Z-score.

binomial

Binomial co-occurrence assessment.

brainerd

Brainerd-Robinson quantitative index.

bray

Sorenson quantitative index.

jaccard

Jaccard qualitative index.

morisita

Morisita-Horn quantitative index.

sorenson

Sorenson qualitative index.

Value

A stats::dist object.

Author(s)

N. Frerebeau

References

Magurran, A. E. (1988). Ecological Diversity and its Measurement. Princeton, NJ: Princeton University Press. doi:10.1007/978-94-015-7358-0.

See Also

index_binomial(), index_brainerd(), index_bray(), index_jaccard(), index_morisita(), index_sorenson()

Other diversity measures: heterogeneity(), occurrence(), profiles(), rarefaction(), richness(), she(), simulate(), turnover()

Examples

## 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

## Sorenson measure (presence/absence data)
similarity(aves, "sorenson") # 0.63

# Jaccard measure (Bray's formula ; count data)
similarity(aves, "bray") # 0.44

# Morisita-Horn measure (count data)
similarity(aves, "morisita") # 0.81