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...to convert the For loop to a more efficient method. It simply loops through a large vector checking if the numeric element is not equal to the index of that element. The following example demonstrates a simplified example: > rows <- 10 > collusionM <- Matrix(0,10,10,sparse=TRUE) > matchM <- matrix(c(1,2,3,4,4,6,7,9,9,10)) > > for (j in 1:rows) if (j != matchM[j]) collusionM[j,matchM[j]] <- collusionM[j,matchM[j]]+1 > collusionM 10 x 10 sparse Matrix of class "dgCMatrix" [1,] . . . . . . . . . . [2,] . . . . . . . . . . [3,] . ....

...sperate) t <- t[order(t$ordin),] # a little accounting for the colors t$PVar <- (t$PVar-min(t$PVar,na.rm=T))/(max(t$PVar,na.rm=T)-min(t $PVar,na.rm=T)) t$col <- round((((t$PVar*100)-100)*-1),0) # t$col is now a collection of integers from 1 to 100 # again, redundancy out of desperation. matchm <- match.map('county',t$mapm,exact=T,warn=T) # define colors with the heat.map palette color <- heat.colors(100)[t$col[matchm]] # alternative (also not working) color <- heat.colors(100)[t$col] # use the colors to fill the map map('county',fill=T,col=color) Michaell Tay...