sediWeighted: Symmetric extremal dependence index (SEDI)
In adamlilith/enmSdm: Tools for Modeling Niches and Distributions of Species

sediWeighted

R Documentation

Symmetric extremal dependence index (SEDI)

Description

This function calculates the symmetric extremal dependence index (SEDI) using a threshold applied to continuous data to demarcate "presence" from "contrast".

Usage

sediWeighted(
  pres,
  contrast,
  presWeight = rep(1, length(pres)),
  contrastWeight = rep(1, length(contrast)),
  thresholds = seq(0, 1, by = 0.01),
  delta = 0.001,
  na.rm = FALSE,
  bg = NULL,
  bgWeight = NULL,
  ...
)

Arguments

`pres`	Numeric vector. Predicted values at presence sites.
`contrast`	Numeric vector. Predicted values at absence/background sites.
`presWeight`	Numeric vector same length as `pres`. Relative weights of presence sites. The default is to assign each presence a weight of 1.
`contrastWeight`	Numeric vector same length as `contrast`. Relative weights of background sites. The default is to assign each presence a weight of 1.
`thresholds`	Numeric vector, Values at which to threshold predictions for calculation of SEDI.
`delta`	Positive numeric >0 in the range [0, 1] and usually very small. This value is used only if calculating the SEDI threshold when any true positive rate or false negative rate is 0 or the false negative rate is 1. Since SEDI uses log(x) and log(1 - x), values of 0 and 1 will produce `NA`s. To obviate this, a small amount can be added to rates that equal 0 and subtracted from rates that equal 1.
`na.rm`	Logical. If `TRUE` then remove any presences and associated weights and absence/background predictions and associated weights with `NA`s.
`bg`	Same as `contrast`. Included for backwards compatibility. Ignored if `contrast` is not `NULL`.
`bgWeight`	Same as `contrastWeight`. Included for backwards compatibility. Ignored if `contrastWeight` is not `NULL`.
`...`	Other arguments (unused).

Value

Numeric value.

References

Wunderlich, R.F., Lin, Y-P., Anthony, J., and Petway, J.R. 2019. Two alternative evaluation metrics to replace the true skill statistic in the assessment of species distribution models. Nature Conservation 35:97-116.

Examples

set.seed(123)
pres <- sqrt(runif(100))
contrast <- runif(10000)
hist(contrast, col='gray', xlim=c(0, 1), breaks=20)
hist(pres, col='green', breaks=20, add=TRUE)
max(sediWeighted(pres, contrast), na.rm=TRUE)
# SEDI is fairly insensitive to weighting (as per Wunderlich et al. 2019)
presWeight <- c(rep(1, 50), rep(1000, 50))
max(sediWeighted(pres, contrast, presWeight=presWeight), na.rm=TRUE)

adamlilith/enmSdm documentation built on Jan. 6, 2023, 11 a.m.