## Not run: ------------------------------------
# ## typical example of PLS-PM in customer satisfaction analysis
# ## model with six LVs and reflective indicators
# ## example of rebus analysis with simulated data
#
# # load data
# data(simdata)
#
# # Calculate plspm
# sim_path = matrix(c(0,0,0,0,0,0,1,1,0), 3, 3, byrow=TRUE)
# dimnames(sim_path) = list(c("Price", "Quality", "Satisfaction"),
# c("Price", "Quality", "Satisfaction"))
# sim_blocks = list(c(1,2,3,4,5), c(6,7,8,9,10), c(11,12,13))
# sim_mod = c("A", "A", "A") # reflective indicators
# sim_global = plspm(simdata, sim_path,
# sim_blocks, modes=sim_mod)
# sim_global
#
# # Cluster analysis on residuals of global model
# sim_clus = res.clus(sim_global)
#
# # Iterative steps of REBUS algorithm on 2 classes
# rebus_sim = it.reb(sim_global, sim_clus, nk=2,
# stop.crit=0.005, iter.max=100)
#
# # apply rebus.test
# sim_permu = rebus.test(sim_global, rebus_sim)
#
# # inspect sim.rebus
# sim_permu
# sim_permu$test_1_2
#
# # or equivalently
# sim_permu[[1]]
#
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