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## Example 1
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# Generates artificial data (a 235X3 matrix with 3 columns: state, region, income).
# The variable 'state' has 2 categories (nc and sc);
# the variable 'region' has 3 categories (1, 2 and 3);
# the variable 'income' is generated using the U(0,1) distribution.
data=rbind(matrix(rep("nc",165),165,1,byrow=TRUE),
matrix(rep("sc",70),70,1,byrow=TRUE))
data=cbind.data.frame(data,c(rep(1,100), rep(2,50), rep(3,15), rep(1,30),rep(2,40)),
1000*runif(235))
names(data)=c("state","region","income")
# the inclusion probabilities are computed using the variable 'income'
pik=inclusionprobabilities(data$income,20)
# draws a sample using systematic sampling (sample size is 20)
s=UPsystematic(pik)
# extracts the observed data
getdata(data,s)
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## Example 2
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# see other examples in 'strata', 'cluster', 'mstage' help files
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