# Required functions: `syrs.est`, `srs.mean`
# required packages: `sampling` (install if needed)

library(sampling)

N=200; n=20; k=10
id=1:200; random=50+4*rnorm(200)
ordered=rnorm(200)+id; periodic=sin(id/5)

plot(random~id,main='random')
plot(ordered~id,main='ordered')
plot(periodic~id,main='periodic')

# syrs.est(data,x,k,n,N,param)

set.seed(5273)
# SRS
s1=srswor(n,N)
srs1=(1:N)[s1==1]
rand.srs=random[srs1]
srs.mean('random',rand.srs,n,N)
# SyRS
syrs1=seq(sample(1:k,1),N,k)
rand.sys=random[syrs1]
syrs.est('random',rand.sys,k,N,'mean')

set.seed(73)
# SRS
s2=srswor(n,N)
srs2=(1:N)[s2==1]
ord.srs=ordered[srs2]
srs.mean('ordered',ord.srs,n,N)
# SyRS
syrs2=seq(sample(1:k,1),N,k)
ord.sys=ordered[syrs2]
syrs.est('ordered',ord.sys,k,N,'mean')

set.seed(590)
# SRS
s3=srswor(n,N)
srs3=(1:N)[s3==1]
per.srs=periodic[srs3]
srs.mean('periodic',per.srs,n,N)
# SyRS
syrs3=seq(sample(1:k,1,replace=F),N,k)
per.sys=periodic[syrs3]
syrs.est('periodic',per.sys,k,N,'mean')