getOverlap | R Documentation |
getOverlap
goes through all m-wise combinations of species
and returns the amount of overlap between species in functions they perform
for each combination
getOverlap( overData, m = 2, type = "positive", index = "sorensen", denom = "set" )
overData |
Matrix of functions and which species affect them from |
m |
Number of functions. Defaults to 2. |
type |
Are the kinds of effects we're looking at "positive", "negative" or "all". |
index |
Type of overlap index to be used. Defaults to "sorenson" but currently incorporates "mountford" and "jaccard" as well. |
denom |
Should the denominator be "all" species or just the "set" of species with the types of interactions being considered? Defaults to "set". |
getOverlap takes a matrix of 1s and -1s, and depending on whether we're interested in positive, negative, or both types of interactions looks for the m-wise overlap between species and returns the overlap index for each combination
Returns a vector of overlap indices.
Jarrett Byrnes.
data(all_biodepth) allVars <- qw(biomassY3, root3, N.g.m2, light3, N.Soil, wood3, cotton3) germany <- subset(all_biodepth, all_biodepth$location == "Germany") vars <- whichVars(germany, allVars) species <- relevantSp(germany, 26:ncol(germany)) # re-normalize N.Soil so that everything is on the # same sign-scale (e.g. the maximum level of a function is the "best" function) germany$N.Soil <- -1 * germany$N.Soil + max(germany$N.Soil, na.rm = TRUE) res.list <- lapply(vars, function(x) sAICfun(x, species, germany)) names(res.list) <- vars redund <- getRedundancy(vars, species, germany) getOverlap(redund, m = 2) getOverlap(redund, m = 2, index = "jaccard") getOverlap(redund, m = 2, index = "mountford") ######### # getOverlap takes a matrix of 1s and -1s, and depending on whether we're # interested in positive, negative, or both types of interactions looks for the # m-wise overlap #########
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