balancedcluster           package:sampling           R Documentation

_B_a_l_a_n_c_e_d _c_l_u_s_t_e_r

_D_e_s_c_r_i_p_t_i_o_n:

     Select a balanced cluster sample and return a matrix that contains
     the vector of inclusion probabilities and the selected sample.

_U_s_a_g_e:

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

_A_r_g_u_m_e_n_t_s:

       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
          equal to 'TRUE'.

  method: the used method in the function samplecube.

_S_e_e _A_l_s_o:

     'samplecube', 'fastflightcube', 'landingcube'

_E_x_a_m_p_l_e_s:

     ############
     ## 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]

