similarity: Similarity

In nfrerebeau/tabula: Analysis and Visualization of Archaeological Count Data

Similarity

Description

Similarity

Usage

similarity(object, ...)

index_jaccard(x, y, ...)

index_sorenson(x, y, ...)

index_bray(x, y, ...)

index_morisita(x, y, ...)

index_brainerd(x, y, ...)

index_binomial(x, y, ...)

## 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")
)

## S4 method for signature 'character,character'
index_jaccard(x, y)

## S4 method for signature 'logical,logical'
index_jaccard(x, y)

## S4 method for signature 'numeric,numeric'
index_jaccard(x, y)

## S4 method for signature 'logical,logical'
index_sorenson(x, y)

## S4 method for signature 'numeric,numeric'
index_sorenson(x, y)

## S4 method for signature 'numeric,numeric'
index_bray(x, y)

## S4 method for signature 'numeric,numeric'
index_morisita(x, y)

## S4 method for signature 'numeric,numeric'
index_brainerd(x, y)

## S4 method for signature 'numeric,numeric'
index_binomial(x, y)

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.
x, y	A length-p numeric vector of count data.
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. This assesses the degree of co-occurrence between taxa/types within a dataset. The strongest associations are shown by large positive numbers, the strongest segregations by large negative numbers.

brainerd

Brainerd-Robinson quantitative index. This is a city-block metric of similarity between pairs of samples/cases.

bray

Sorenson quantitative index (Bray and Curtis modified version of the Sorenson index).

jaccard

Jaccard qualitative index.

morisita

Morisita-Horn quantitative index.

sorenson

Sorenson qualitative index.

Value

• similarity() returns a stats::dist object.

• ⁠index_*()⁠ return a numeric vector.

Author(s)

N. Frerebeau

References

Brainerd, G. W. (1951). The Place of Chronological Ordering in Archaeological Analysis. American Antiquity, 16(04), 301-313. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/276979")}.

Bray, J. R. & Curtis, J. T. (1957). An Ordination of the Upland Forest Communities of Southern Wisconsin. Ecological Monographs, 27(4), 325-349. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/1942268")}.

Kintigh, K. (2006). Ceramic Dating and Type Associations. In J. Hantman and R. Most (eds.), Managing Archaeological Data: Essays in Honor of Sylvia W. Gaines. Anthropological Research Paper, 57. Tempe, AZ: Arizona State University, p. 17-26.

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")}.

Robinson, W. S. (1951). A Method for Chronologically Ordering Archaeological Deposits. American Antiquity, 16(04), 293-301. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/276978")}.

See Also

Other diversity measures: heterogeneity(), occurrence(), rarefaction(), richness(), 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

nfrerebeau/tabula documentation built on March 3, 2024, 11:24 p.m.