# NOT RUN {
### EXAMPLE 1 ###
### generate simulated data ###
set.seed(666)
N=1000
SIMDATA<-matrix(0,N,3)
SIMDATA<-as.data.frame(SIMDATA)
names(SIMDATA)<-c("plotID","Observed","Predicted")
SIMDATA$plotID<-1:N
SIMDATA$Observed<-rbinom(n=N,size=1,prob=.2)
SIMDATA$Predicted[SIMDATA$Observed==1]<-rnorm(n=length(SIMDATA$Observed[SIMDATA$Observed==1]),mean=.8,sd=.15)
SIMDATA$Predicted[SIMDATA$Observed==0]<-rnorm(n=length(SIMDATA$Observed[SIMDATA$Observed==0]),mean=.2,sd=.15)
SIMDATA$Predicted<-(SIMDATA$Predicted-min(SIMDATA$Predicted))/(max(SIMDATA$Predicted)-min(SIMDATA$Predicted))
### plot simulated data
hist(SIMDATA$Predicted,100)
### calculate confusion matrix ###
cmx(SIMDATA)
### EXAMPLE 2 ###
data(SIM3DATA)
cmx(SIM3DATA)
cmx(SIM3DATA,which.model=2)
cmx(SIM3DATA,which.model=3,threshold=.2)
# }
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