BBWO_MahalHSIs <- function(lndscp, nest.samples = BBWO_nest_samples) {
BC1.HSI <- TBC1.HSI <- TB1.HSI <- numeric(length=nrow(lndscp))
for (y in 1:length(nest.samples)) {
Recs <- nest.samples[[y]]
#BC1 model ################################################################################
Lnd <- as.matrix(lndscp[,c("DNBR","LOCCC40","LANDCC40")])
Loc <- as.matrix(Recs[,c("DNBR","LOCCC40","LANDCC40")])
M <- HSI_Mahal(Loc,Lnd)
BC1.HSI <- BC1.HSI + round(M,digits=4)
#TBC1 model ################################################################################
Lnd<-as.matrix(lndscp[,c("COSASP","DNBR","LOCCC40","LANDCC40")])
Loc<-as.matrix(Recs[,c("COSASP","DNBR","LOCCC40","LANDCC40")])
M <- HSI_Mahal(Loc,Lnd)
TBC1.HSI <- TBC1.HSI + round(M,digits=4)
#TB1 model ################################################################################
Lnd<-as.matrix(lndscp[,c("COSASP","DNBR")])
Loc<-as.matrix(Recs[,c("COSASP","DNBR")])
M <- HSI_Mahal(Loc,Lnd)
TB1.HSI <- TB1.HSI + round(M,digits=4)
}
#Calculate HSI means and s.e.'s across model replicates
BC1.HSI <- BC1.HSI/100
TBC1.HSI <- TBC1.HSI/100
TB1.HSI <- TB1.HSI/100
Data <- cbind(lndscp, BC1.HSI, TBC1.HSI, TB1.HSI) #Bind cell IDs and spatial coordinates to matrix with HSI scores.
dimnames(Data)[[2]][(ncol(Data) - 2):ncol(Data)] <- c("BC1","TBC1","TB1")
return(Data)
}
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