CorIndex.TargetVar: CorIndex.TargetVar is creates the variables that are...
In Zabados/PhiCor: PhiCor: Calculating the Phi coefficient of Association

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

This function is usually called by other function, but could be run seperatly to give many of the variables which go into the equations to calculate the phi coefficent. This is useful if manually checking the calculation.

1	CorIndex.TargetVar(CorIndexVarInput, targetgroup)

`CorIndexVarInput`	is the custom class "CorIndexVar" output from CorIndex
`targetgroup`	Integer - ID of the habitat of interest.

a custom class "CorIndexVar" containing all values which are the same for all habitats and don't need to be recalculated for every habitat and the ones for the specific target habitat. Including those from CorIndex Nk, nk, the habitats "GroupDF", N, K, Ngp, nkoverNk ng & n and aditionally np, Np & ngp See De Cáceres and Legendre (2009) This is reused to give all the results later.

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).

CorIndex

    #Builing on the examples from \link[PhiCor]{CorIndex}
    #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 CorIndex. In this case we are interested in
    #habitat 1 (using the ID for the habitat)
    Inputs_species1_hab1 = CorIndex.TargetVar(Inputs_species1, 1)


    #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 = CorIndex.TargetVar(Inputs_species2, 4)