balancedcluster: Balanced cluster

In sampling: Survey Sampling

Balanced cluster

Description

Selects a balanced cluster sample.

Usage

balancedcluster(X,m,cluster,selection=1,comment=TRUE,method=1)

Arguments

X	matrix of auxiliary variables on which the sample must be balanced.
m	number of clusters to be selected.
cluster	vector of integers that defines the clusters.
selection	1, selection of the clusters with probabilities proportional to size, 2, selection of the clusters with equal probabilities.
comment	a comment is written during the execution if comment is TRUE.
method	the used method in the function samplecube.

Value

Returns a matrix containing the vector of inclusion probabilities and the selected sample.

See Also

samplecube, fastflightcube, landingcube

Examples

############
## Example 1
############
# definition of the clusters; there are 15 units in 3 clusters
cluster=c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,3)
# matrix of balancing variables
X=cbind(c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15))
# selection of 2 clusters
s=balancedcluster(X,2,cluster,2,TRUE)
# the sample of clusters with the inclusion probabilities of the clusters
s
# the selected clusters
unique(cluster[s[,1]==1])
# the selected units 
(1:length(cluster))[s[,1]==1]
# with the probabilities
s[s[,1]==1,2]
############
## Example 2
############
data(MU284)
X=cbind(MU284$P75,MU284$CS82,MU284$SS82,MU284$S82,MU284$ME84)
s=balancedcluster(X,10,MU284$CL,1,TRUE)
cluster=MU284$CL
# the selected clusters
unique(cluster[s[,1]==1])
# the selected units 
(1:length(cluster))[s[,1]==1]
# with the probabilities
s[s[,1]==1,2]

sampling documentation built on Nov. 2, 2023, 6:26 p.m.