library(BalancedSampling)
N <- 200
n <- 10
p <- 3
i <- 100
set.seed(i)
x <- matrix(rnorm(N*p),ncol=p)
prob <- rep(n/N,N)
set.seed(i)
y <- scps(prob,x)
#set.seed(i)
#y_kdtree <- lpm2_kdtree(prob,x)
#
#print( sum(y != y_kdtree) )
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