simFromSetOps: Calculate similarity from set operations

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/simFromSetOps.R

Description

This function calculates pair-wise similarity based on the results of set operations (intersection, union) among the subjects.

Usage

1
2
3
simFromSetOps(size1, size2, intersection, union, total.size = NULL, 
method = c("Jaccard", "Sorensen", "Simpson", "Baroni"), 
verbosity = 1)

Arguments

size1

size of subject 1 (e.g., area of the distribution range of a species, or its number of presences within a grid). Not needed if method = "Jaccard".

size2

the same for subject 2.

intersection

size of the intersection among subjects 1 and 2 (area of the intersection among their distribution ranges, or number of grid cells in which they co-occur).

union

size of the union of subjects 1 and 2.

total.size

total size of the study area. Needed only when calculating a similarity index that takes shared absences into account (i.e., method = "Baroni").

method

the similarity index to use. Currently implemented options are "Jaccard", "Sorensen", "Simpson" or "Baroni".

verbosity

integer indicating whether to display messages.

Details

Similarities among ecological communities, beta diversity patterns, biotic regions, and distributional relationships among species are commonly determined based on pair-wise (dis)similarities in species' occurrence patterns. This function implements some of the most commonly employed similarity indices, namely those of Jaccard (1901), Sorensen (1948), Simpson (1960) and Baroni-Urbani & Buser (1976), based on the amount of occupied and overlap area between two species.

Value

The numeric value of similarity among subjects 1 and 2.

Author(s)

A. Marcia Barbosa

References

Baroni-Urbani C. & Buser M.W. (1976) Similarity of Binary Data. Systematic Zoology, 25: 251-259

Jaccard P. (1901) Etude comparative de la distribution florale dans une portion des Alpes et des Jura. Memoires de la Societe Vaudoise des Sciences Naturelles, 37: 547-579

Simpson, G.G. (1960) Notes on the measurement of faunal resemblance. Amer. J. Sci. 258A, 300-311

Sorensen T. (1948) A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on Danish commons. Kongelige Danske Videnskabernes Selskab, 5(4): 1-34

See Also

fuzSim, simMat

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
# take two species which occur in 22 and 35 area units, respectively
# and which overlap in 8 of those units:

sp1 <- 22
sp2 <- 35
int <- 8
uni <- sp1 + sp2 - int


# calculate similarity between their distributions based on 
# different indices:

simFromSetOps(intersection = int, union = uni, method = "Jaccard")

simFromSetOps(sp1, sp2, int, uni, method = "Sorensen")

simFromSetOps(sp1, sp2, int, uni, method = "Simpson")


# if you want Baroni-Urbani & Buser's index
# you need to provide also the total size of your study area:

simFromSetOps(sp1, sp2, int, uni, total = 100, method = "Baroni")

fuzzySim documentation built on Feb. 4, 2020, 5:06 p.m.