Description Usage Arguments Value Author(s) References See Also Examples
View source: R/CorrelationIndex.R
This function calculates the non group-equalised version of the habitat indicator value (IndVal) De Cáceres and Legendre (2009). This is useful alone to calculate the non group-equalised version for a single habitat of interest among multiple other habitats.
1 | Indicator.nonEqual(CorIndexTargetVarInput)
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CorIndexTargetVarInput |
a custom class "CorIndexVar" containing all values from from both CorIndex and CorIndex.TargetVar |
IndVal - a floating point number between 0 and 1.
Jordan Chetcuti
De Cáceres, M., & Legendre, P. (2009). Associations between species and groups of sites: indices and statistical inference. Ecology, 90(12), 3566–3574.
Chetcuti, J., Kunin, W. E. & Bullock, J. M. A weighting method to improve habitat association analysis: tested on British carabids. Ecography (Cop.). 42, 1395–1404 (2019).
PhiCor
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | #Builing on the examples from \link[PhiCor]{CorIndex.TargetVar}
#Using the included dataframe Species1
Inputs_species1 = CorIndex(InDataframe = Species1, speciesbinary = 'Species1', weighted = 'Proportion', group = 'HabId', 'LocationID')
Inputs_species1$nkoverNk
#Using CorIndex.TargetVar, the input is the output of Indicator. In this case we are interested in
#habitat 1 (using the ID for the habitat)
Inputs_species1_hab1 = Indicator.TargetVar(Inputs_species1, 1)
species1_hab1_Phi = Indicator.nonEqual(Inputs_species1_hab1)
#Using the included dataframe Species2
#If you wanted the analysis to be non-weighted.
Species2Unweight = Species2[which(Species2$Proportion==1),]
#This analysis is then the unweighted version of the analysis. SquareID is not needed.
Inputs_species2 = CorIndex(InDataframe = Species2Unweight, speciesbinary = 'Species2', weighted = 'Proportion', group = 'HabId')
names(Inputs_species2)
#Looking at habitat 4
Inputs_species2_hab4 = Indicator.TargetVar(Inputs_species2, 4)
species2_hab4_IndVal = Indicator.nonEqual(Inputs_species2_hab4)
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