##### Plot results # load('Results/correct_rank_91415.RData') nvics = dim(correct_rank)[1] correct_rank1 = correct_rank[,length(lambdas)] # demographics model correct_rank2 = correct_rank[,1] # cascade model lambda_opt = which.max(colMeans(correct_rank<1382)) correct_rank3 = correct_rank[,lambda_opt] # best combined model popsizes = c(0.1,0.5,1.0)/100 vcount(lcc)*popsizes counts = matrix(c( sum(correct_rank1<(vcount(lcc)*popsizes[1])), sum(correct_rank1<(vcount(lcc)*popsizes[2])), sum(correct_rank1<(vcount(lcc)*popsizes[3])), sum(correct_rank2<(vcount(lcc)*popsizes[1])), sum(correct_rank2<(vcount(lcc)*popsizes[2])), sum(correct_rank2<(vcount(lcc)*popsizes[3])), sum(correct_rank3<(vcount(lcc)*popsizes[1])), sum(correct_rank3<(vcount(lcc)*popsizes[2])), sum(correct_rank3<(vcount(lcc)*popsizes[3]))), nrow=3, byrow=T) barplot(counts, xlab="Size of High-Risk Population", ylab="Victims Predicted", names.arg=paste(as.character(popsizes*100),'%',sep=''), ylim=c(0,max(counts)*1.1),axes=F, col=c(rgb(0,0,1,1/2),rgb(1,0,0,1/2),rgb(0,1,0,1/2)), beside=TRUE) axis(2, at=pretty(counts*100/nvics)*nvics/100, lab=paste0(pretty(counts*100/nvics), "%"), las=TRUE) legend("topleft", inset=0.05, c("Demographics Model", "Contagion Model", "Combined Model"), fill=c(rgb(0,0,1,1/2),rgb(1,0,0,1/2),rgb(0,1,0,1/2))) box(which='plot') par(new=T) barplot(counts, ylim=c(0,max(counts)*1.1), col=c(rgb(0,0,1,0),rgb(1,0,0,0),rgb(0,1,0,0)), beside=TRUE,axes=F) axis(side=4, at=pretty(counts), lab=pretty(counts)) mtext(side = 4, line = 3, "Number of Victims Predicted") #### Precision-Recall Curve plot(ecdf(correct_rank1),col='red',lwd=2,main='') plot(ecdf(correct_rank2),col='darkblue',lwd=2,add=T) plot(ecdf(correct_rank3),col='darkgreen',lwd=2,add=T) legend("bottomright", inset=0.05, c("Demographics Model", "Cascade Model", "Combined Model"), fill=c('red','darkblue','darkgreen'))