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ericpgreen/simord.R

Last active December 26, 2015 04:09
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code for simulating a multivariate ordinal dataset using the MultiOrd package and resulting dataset
Raw
simord.R
# info
#-------------------------------------------------------------------------------------
# simulation of a multivariate ordinal dataset using the MultiOrd package
# running this .R gist will *only* read in the final data, not run the simulation
# scroll down to see original code to simulate
# sim code modified by package creator to override simBinCorr function
# simulated data
#-------------------------------------------------------------------------------------
mydata <- structure(list(v1 = c(3L, 2L, 1L, 1L, 3L, 2L, 3L, 3L, 3L, 2L,
2L, 2L, 1L, 3L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 3L, 1L, 2L, 1L, 3L,
4L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 2L, 2L, 3L, 2L, 1L, 3L,
3L, 3L, 3L, 2L, 4L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 2L, 2L, 2L,
3L, 3L, 3L, 2L, 3L, 3L, 2L, 2L, 4L, 1L, 2L, 3L, 4L, 3L, 3L, 1L,
2L, 2L, 2L, 3L, 3L, 1L, 3L, 3L, 2L, 2L, 4L, 3L, 1L, 4L, 3L, 3L,
1L, 3L, 2L, 3L, 3L, 3L, 3L, 2L, 4L, 2L, 2L, 1L, 1L, 2L, 2L, 3L,
2L, 3L, 3L, 3L, 1L, 3L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 3L, 3L,
1L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 4L, 3L,
3L, 1L, 3L, 1L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 3L, 3L,
3L, 1L, 3L, 2L, 3L, 2L, 4L, 2L, 3L, 2L, 3L, 2L, 3L, 1L, 2L, 3L,
2L, 3L, 2L, 3L, 1L, 4L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 3L, 4L,
3L, 3L, 1L, 2L, 3L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 1L, 3L, 2L, 3L,
1L, 4L, 3L, 3L, 2L, 2L, 3L, 3L, 4L, 2L, 2L, 2L, 2L, 2L, 4L, 2L,
2L, 2L, 3L, 2L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 2L,
3L, 2L, 3L, 1L, 2L, 2L, 2L, 2L, 3L, 4L, 3L, 2L, 3L, 2L, 3L, 3L,
3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 4L, 2L, 2L, 3L, 3L, 1L,
2L, 4L, 3L, 1L, 2L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L,
4L, 3L, 4L, 3L, 2L, 1L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 3L, 4L, 1L,
2L, 2L, 4L, 2L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 4L,
3L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 2L,
2L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 2L, 2L, 3L, 2L,
2L, 3L, 3L, 2L, 2L, 2L, 4L, 2L, 3L, 2L, 3L, 3L, 3L, 2L, 2L, 3L,
1L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 1L, 3L, 2L,
2L, 2L, 3L, 2L, 4L, 3L, 3L, 2L, 4L, 2L, 2L, 2L, 2L, 2L, 3L, 2L,
3L, 1L, 2L, 2L, 3L, 4L, 1L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 1L,
2L, 3L, 1L, 3L, 3L, 3L, 1L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 1L, 3L,
4L, 3L, 3L, 2L, 2L, 1L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 2L, 3L,
2L, 3L, 3L, 2L, 4L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 2L, 3L, 3L,
2L, 2L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 3L, 4L, 3L, 2L, 2L,
3L, 2L, 4L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 1L, 3L, 3L, 2L, 1L, 3L,
3L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L), v2 = c(4L, 1L, 3L, 2L,
3L, 2L, 4L, 4L, 3L, 2L, 3L, 1L, 2L, 3L, 1L, 1L, 2L, 1L, 1L, 2L,
1L, 3L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 2L, 3L,
2L, 2L, 2L, 4L, 2L, 2L, 2L, 4L, 2L, 2L, 3L, 3L, 4L, 3L, 2L, 2L,
4L, 3L, 3L, 1L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 2L, 3L, 3L, 2L,
2L, 4L, 2L, 3L, 3L, 2L, 1L, 2L, 2L, 4L, 2L, 2L, 3L, 3L, 2L, 2L,
3L, 3L, 3L, 2L, 3L, 3L, 4L, 3L, 4L, 2L, 3L, 3L, 3L, 2L, 4L, 2L,
3L, 1L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 2L, 2L,
3L, 2L, 3L, 2L, 3L, 3L, 2L, 4L, 3L, 3L, 4L, 2L, 3L, 3L, 1L, 2L,
2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 4L, 2L,
4L, 1L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 2L, 3L, 2L, 3L, 3L,
2L, 1L, 3L, 2L, 3L, 4L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 4L, 4L, 2L, 3L, 4L, 1L, 3L, 3L, 3L, 4L,
2L, 3L, 1L, 4L, 2L, 3L, 2L, 3L, 4L, 3L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 2L, 2L, 2L, 3L, 2L, 2L, 4L, 3L, 1L, 3L, 3L, 2L, 4L, 1L, 3L,
2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 1L, 2L, 2L, 2L, 2L, 4L, 2L,
3L, 2L, 4L, 2L, 3L, 3L, 4L, 2L, 3L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L, 2L, 4L, 3L, 3L, 2L, 2L, 4L, 3L, 3L, 3L, 4L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 2L, 4L, 2L,
3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 4L, 3L, 2L, 4L, 3L, 2L, 2L, 4L,
2L, 2L, 2L, 1L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 4L, 2L,
1L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 3L, 3L, 2L, 2L, 3L, 3L,
3L, 3L, 2L, 2L, 3L, 2L, 1L, 4L, 3L, 2L, 2L, 2L, 3L, 2L, 4L, 2L,
2L, 2L, 3L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 4L, 2L, 2L, 2L, 3L,
3L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 1L, 4L, 2L,
2L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 2L, 2L, 4L, 3L, 3L, 3L, 2L, 3L,
2L, 1L, 2L, 2L, 3L, 3L, 2L, 2L, 1L, 3L, 3L, 4L, 2L, 3L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 4L, 3L, 3L, 2L, 2L, 2L, 4L, 3L, 3L, 1L,
1L, 3L, 3L, 3L, 1L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 3L,
1L, 2L, 2L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 4L, 1L, 3L, 2L, 3L, 1L,
3L, 3L, 3L, 1L, 2L, 1L, 3L, 2L, 3L, 3L, 3L, 2L, 2L, 1L, 2L, 2L,
2L, 3L, 2L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L
), v3 = c(3L, 2L, 4L, 1L, 4L, 2L, 3L, 3L, 3L, 2L, 1L, 2L, 1L,
3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 1L, 2L, 2L, 2L, 3L, 3L, 3L,
2L, 3L, 3L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 3L, 4L,
2L, 3L, 2L, 3L, 3L, 2L, 3L, 4L, 3L, 1L, 2L, 2L, 2L, 3L, 4L, 3L,
2L, 3L, 2L, 2L, 2L, 3L, 2L, 1L, 3L, 3L, 4L, 3L, 2L, 2L, 2L, 2L,
1L, 3L, 2L, 3L, 3L, 1L, 1L, 4L, 3L, 2L, 2L, 3L, 3L, 1L, 4L, 3L,
1L, 3L, 3L, 4L, 2L, 3L, 3L, 4L, 2L, 2L, 2L, 2L, 3L, 1L, 3L, 4L,
4L, 2L, 4L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 3L, 3L, 2L, 3L, 3L,
3L, 3L, 2L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 3L,
2L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 4L,
2L, 3L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 2L, 2L, 1L,
3L, 2L, 3L, 1L, 2L, 2L, 3L, 2L, 1L, 1L, 2L, 2L, 3L, 4L, 3L, 2L,
2L, 4L, 2L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 3L,
3L, 2L, 2L, 3L, 3L, 4L, 2L, 2L, 4L, 2L, 1L, 3L, 2L, 2L, 1L, 3L,
2L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 4L, 3L, 3L, 2L, 1L, 3L, 3L,
1L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 3L, 1L, 3L, 3L, 3L, 2L, 3L,
2L, 2L, 2L, 2L, 2L, 4L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 3L, 3L, 3L,
3L, 2L, 2L, 1L, 2L, 3L, 2L, 3L, 2L, 4L, 4L, 3L, 2L, 2L, 1L, 3L,
3L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 1L,
2L, 2L, 3L, 2L, 1L, 4L, 2L, 1L, 3L, 2L, 2L, 3L, 1L, 2L, 2L, 4L,
3L, 2L, 3L, 2L, 3L, 3L, 3L, 4L, 2L, 1L, 1L, 3L, 1L, 1L, 3L, 3L,
2L, 2L, 2L, 3L, 2L, 3L, 3L, 4L, 2L, 3L, 2L, 2L, 3L, 3L, 3L, 4L,
3L, 3L, 2L, 2L, 1L, 2L, 2L, 3L, 2L, 4L, 3L, 3L, 2L, 1L, 2L, 3L,
2L, 3L, 3L, 3L, 1L, 3L, 2L, 2L, 1L, 1L, 2L, 3L, 2L, 4L, 2L, 2L,
2L, 4L, 3L, 2L, 2L, 2L, 3L, 2L, 4L, 1L, 2L, 3L, 2L, 1L, 2L, 3L,
4L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
2L, 2L, 2L, 3L, 3L, 4L, 2L, 1L, 3L, 3L, 3L, 2L, 2L, 1L, 3L, 3L,
2L, 3L, 2L, 1L, 1L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 1L, 1L,
2L, 3L, 2L, 3L, 2L, 4L, 2L, 3L, 3L, 2L, 3L, 1L, 2L, 4L, 2L, 3L,
2L, 3L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 3L, 2L, 2L, 4L, 3L, 3L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 2L), v4 = c(4L, 2L, 4L, 2L, 4L, 2L, 3L,
1L, 3L, 4L, 1L, 3L, 1L, 4L, 2L, 1L, 1L, 2L, 1L, 3L, 2L, 4L, 1L,
3L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 3L, 4L, 1L, 2L, 3L, 1L, 3L, 4L,
4L, 1L, 1L, 4L, 4L, 1L, 1L, 2L, 3L, 4L, 4L, 3L, 3L, 3L, 3L, 3L,
2L, 3L, 2L, 4L, 3L, 3L, 2L, 1L, 3L, 2L, 2L, 4L, 1L, 2L, 4L, 4L,
3L, 4L, 1L, 3L, 1L, 4L, 2L, 4L, 4L, 4L, 3L, 1L, 2L, 3L, 3L, 3L,
1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 4L, 4L, 4L, 1L, 1L,
1L, 2L, 4L, 2L, 4L, 4L, 3L, 2L, 4L, 2L, 3L, 1L, 4L, 4L, 3L, 2L,
2L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 1L, 3L, 4L, 3L, 2L, 1L, 1L, 2L,
1L, 3L, 4L, 4L, 2L, 4L, 1L, 4L, 3L, 1L, 3L, 1L, 1L, 2L, 1L, 2L,
1L, 4L, 4L, 4L, 2L, 3L, 1L, 4L, 2L, 4L, 2L, 3L, 3L, 3L, 2L, 3L,
2L, 1L, 3L, 2L, 3L, 2L, 4L, 2L, 3L, 4L, 2L, 4L, 4L, 2L, 1L, 2L,
1L, 1L, 3L, 3L, 3L, 4L, 2L, 3L, 3L, 2L, 4L, 4L, 4L, 2L, 4L, 1L,
4L, 3L, 3L, 2L, 3L, 3L, 2L, 1L, 1L, 4L, 3L, 3L, 1L, 4L, 1L, 2L,
1L, 3L, 2L, 4L, 2L, 4L, 4L, 3L, 4L, 4L, 2L, 2L, 4L, 4L, 4L, 4L,
4L, 2L, 1L, 4L, 4L, 4L, 3L, 4L, 1L, 4L, 1L, 4L, 3L, 3L, 4L, 4L,
2L, 4L, 4L, 3L, 4L, 4L, 1L, 2L, 1L, 2L, 1L, 1L, 3L, 4L, 2L, 2L,
4L, 4L, 3L, 2L, 2L, 2L, 3L, 4L, 4L, 1L, 1L, 2L, 2L, 4L, 2L, 3L,
2L, 1L, 1L, 4L, 2L, 4L, 3L, 1L, 4L, 1L, 2L, 4L, 1L, 1L, 4L, 4L,
4L, 4L, 1L, 1L, 1L, 4L, 4L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 2L, 2L,
2L, 1L, 4L, 4L, 3L, 1L, 4L, 4L, 4L, 2L, 1L, 4L, 2L, 1L, 3L, 2L,
1L, 2L, 4L, 2L, 4L, 4L, 2L, 3L, 1L, 4L, 2L, 3L, 4L, 4L, 3L, 3L,
3L, 4L, 1L, 1L, 4L, 4L, 2L, 2L, 1L, 1L, 2L, 4L, 2L, 4L, 1L, 3L,
2L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 2L, 2L, 1L, 4L, 4L, 4L, 1L, 4L,
4L, 4L, 2L, 2L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 4L, 1L, 1L, 2L, 2L,
1L, 3L, 2L, 3L, 1L, 1L, 4L, 4L, 3L, 1L, 3L, 2L, 4L, 4L, 4L, 1L,
4L, 4L, 3L, 2L, 3L, 1L, 4L, 3L, 4L, 2L, 3L, 1L, 4L, 1L, 1L, 2L,
4L, 4L, 4L, 4L, 3L, 3L, 1L, 4L, 1L, 3L, 4L, 4L, 3L, 1L, 4L, 3L,
1L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 1L, 2L, 2L, 4L, 2L, 1L, 4L,
3L, 4L, 4L, 2L, 3L, 2L, 2L, 4L, 1L, 3L, 1L, 4L, 1L, 2L, 3L, 4L,
1L, 4L, 4L, 4L, 2L, 4L, 3L, 4L, 1L, 3L, 1L, 1L, 2L, 1L, 4L, 3L,
2L, 1L, 4L, 4L, 4L, 2L, 1L, 1L, 2L, 4L, 2L, 2L, 1L), v5 = c(3L,
4L, 4L, 1L, 1L, 2L, 3L, 1L, 4L, 4L, 2L, 3L, 4L, 3L, 2L, 2L, 1L,
4L, 1L, 4L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 3L, 3L, 4L, 4L, 1L, 3L,
3L, 4L, 3L, 4L, 4L, 4L, 1L, 2L, 1L, 4L, 3L, 3L, 1L, 1L, 3L, 4L,
4L, 2L, 3L, 4L, 4L, 2L, 1L, 3L, 1L, 4L, 4L, 4L, 1L, 1L, 2L, 1L,
2L, 4L, 1L, 2L, 2L, 4L, 3L, 3L, 1L, 4L, 2L, 4L, 1L, 4L, 3L, 1L,
4L, 2L, 4L, 4L, 4L, 2L, 1L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
1L, 1L, 4L, 4L, 2L, 3L, 1L, 4L, 4L, 2L, 4L, 4L, 2L, 4L, 3L, 4L,
4L, 1L, 4L, 3L, 4L, 2L, 1L, 4L, 3L, 4L, 3L, 2L, 4L, 3L, 1L, 4L,
4L, 2L, 4L, 4L, 4L, 3L, 2L, 4L, 3L, 4L, 4L, 4L, 2L, 4L, 4L, 4L,
4L, 2L, 2L, 1L, 4L, 4L, 2L, 3L, 4L, 4L, 4L, 1L, 1L, 4L, 4L, 3L,
2L, 4L, 3L, 4L, 1L, 3L, 2L, 2L, 3L, 1L, 3L, 1L, 4L, 2L, 4L, 3L,
2L, 4L, 4L, 1L, 1L, 2L, 2L, 1L, 4L, 3L, 4L, 4L, 2L, 3L, 3L, 2L,
4L, 4L, 2L, 2L, 4L, 2L, 4L, 4L, 4L, 1L, 3L, 3L, 3L, 2L, 1L, 3L,
3L, 4L, 1L, 3L, 2L, 4L, 2L, 3L, 2L, 4L, 2L, 3L, 4L, 3L, 3L, 1L,
2L, 4L, 4L, 3L, 4L, 4L, 3L, 2L, 3L, 4L, 3L, 4L, 4L, 4L, 2L, 4L,
1L, 4L, 3L, 1L, 4L, 3L, 2L, 4L, 3L, 4L, 4L, 4L, 1L, 1L, 2L, 1L,
2L, 2L, 3L, 4L, 1L, 2L, 1L, 4L, 3L, 2L, 1L, 1L, 4L, 4L, 3L, 1L,
1L, 4L, 4L, 4L, 2L, 4L, 1L, 2L, 3L, 4L, 1L, 1L, 4L, 2L, 4L, 2L,
2L, 3L, 1L, 2L, 4L, 4L, 4L, 4L, 1L, 3L, 2L, 2L, 1L, 3L, 3L, 4L,
1L, 3L, 3L, 4L, 2L, 2L, 1L, 4L, 3L, 1L, 3L, 1L, 3L, 1L, 4L, 3L,
1L, 3L, 4L, 2L, 3L, 2L, 2L, 2L, 3L, 1L, 3L, 4L, 1L, 4L, 1L, 4L,
3L, 2L, 4L, 4L, 4L, 4L, 4L, 3L, 1L, 2L, 3L, 4L, 2L, 3L, 2L, 4L,
2L, 4L, 1L, 4L, 4L, 4L, 2L, 4L, 4L, 4L, 4L, 1L, 3L, 3L, 2L, 2L,
1L, 2L, 4L, 4L, 4L, 4L, 3L, 4L, 2L, 4L, 4L, 3L, 4L, 1L, 3L, 4L,
4L, 4L, 4L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 1L, 2L, 4L, 4L, 4L, 3L,
3L, 1L, 4L, 2L, 4L, 4L, 2L, 2L, 3L, 4L, 4L, 1L, 3L, 4L, 2L, 3L,
4L, 1L, 4L, 2L, 4L, 1L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 4L, 3L, 1L,
3L, 4L, 4L, 1L, 4L, 4L, 2L, 4L, 3L, 3L, 4L, 4L, 3L, 4L, 3L, 3L,
2L, 2L, 4L, 1L, 1L, 3L, 3L, 4L, 3L, 4L, 3L, 3L, 1L, 3L, 1L, 4L,
1L, 4L, 4L, 1L, 3L, 4L, 2L, 4L, 3L, 4L, 4L, 3L, 3L, 4L, 2L, 4L,
1L, 4L, 4L, 4L, 2L, 3L, 2L, 1L, 3L, 3L, 4L, 1L, 1L, 1L, 1L, 4L,
3L, 2L, 2L), v6 = c(3L, 3L, 2L, 2L, 1L, 2L, 4L, 2L, 3L, 4L, 2L,
4L, 2L, 3L, 4L, 1L, 1L, 3L, 2L, 4L, 1L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 3L, 3L, 1L, 4L, 4L, 1L, 4L, 4L, 4L, 3L, 3L, 1L, 2L, 1L, 4L,
3L, 1L, 1L, 1L, 4L, 4L, 4L, 3L, 4L, 4L, 3L, 2L, 2L, 4L, 1L, 3L,
1L, 4L, 2L, 2L, 4L, 2L, 1L, 3L, 2L, 2L, 4L, 4L, 2L, 4L, 2L, 4L,
4L, 4L, 1L, 3L, 3L, 3L, 4L, 1L, 3L, 3L, 4L, 2L, 4L, 3L, 3L, 4L,
3L, 3L, 4L, 3L, 4L, 1L, 2L, 4L, 3L, 3L, 1L, 3L, 1L, 1L, 3L, 2L,
3L, 4L, 1L, 4L, 1L, 4L, 3L, 2L, 4L, 4L, 4L, 2L, 2L, 3L, 4L, 3L,
4L, 3L, 3L, 4L, 2L, 4L, 4L, 4L, 4L, 3L, 2L, 4L, 2L, 4L, 4L, 4L,
4L, 4L, 2L, 4L, 2L, 2L, 3L, 2L, 1L, 3L, 3L, 4L, 2L, 3L, 4L, 4L,
1L, 2L, 1L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 1L, 4L, 1L, 1L, 4L, 1L,
3L, 1L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L, 2L, 2L, 2L, 2L, 4L, 3L,
4L, 3L, 2L, 4L, 4L, 2L, 4L, 4L, 1L, 2L, 4L, 2L, 4L, 4L, 4L, 1L,
3L, 4L, 1L, 2L, 1L, 4L, 4L, 4L, 1L, 4L, 2L, 3L, 1L, 3L, 1L, 3L,
2L, 4L, 3L, 4L, 3L, 1L, 1L, 3L, 4L, 3L, 4L, 3L, 4L, 2L, 1L, 4L,
4L, 3L, 3L, 4L, 1L, 3L, 4L, 4L, 3L, 1L, 4L, 4L, 2L, 4L, 4L, 3L,
4L, 3L, 1L, 2L, 2L, 1L, 2L, 2L, 4L, 4L, 2L, 3L, 3L, 4L, 4L, 4L,
2L, 1L, 3L, 4L, 4L, 1L, 4L, 3L, 4L, 4L, 1L, 3L, 3L, 2L, 2L, 4L,
2L, 3L, 3L, 1L, 4L, 2L, 1L, 4L, 2L, 2L, 3L, 3L, 4L, 2L, 1L, 1L,
1L, 4L, 4L, 1L, 4L, 1L, 2L, 1L, 4L, 3L, 1L, 1L, 2L, 2L, 1L, 2L,
1L, 2L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 4L, 4L, 2L,
4L, 4L, 2L, 4L, 1L, 3L, 2L, 3L, 3L, 4L, 4L, 4L, 3L, 4L, 2L, 1L,
3L, 4L, 2L, 1L, 2L, 4L, 1L, 1L, 2L, 3L, 1L, 3L, 2L, 4L, 3L, 4L,
4L, 1L, 3L, 4L, 3L, 2L, 1L, 2L, 4L, 2L, 3L, 1L, 4L, 3L, 1L, 2L,
4L, 3L, 4L, 2L, 3L, 4L, 4L, 4L, 3L, 2L, 2L, 2L, 1L, 1L, 2L, 3L,
2L, 1L, 3L, 4L, 3L, 1L, 3L, 4L, 4L, 2L, 4L, 1L, 4L, 2L, 4L, 1L,
4L, 2L, 2L, 4L, 1L, 1L, 4L, 4L, 4L, 2L, 4L, 2L, 4L, 4L, 1L, 3L,
3L, 4L, 3L, 4L, 4L, 1L, 4L, 4L, 4L, 1L, 4L, 4L, 4L, 3L, 3L, 3L,
3L, 4L, 4L, 3L, 4L, 4L, 1L, 2L, 4L, 2L, 4L, 4L, 4L, 4L, 3L, 4L,
4L, 3L, 2L, 4L, 1L, 3L, 1L, 3L, 2L, 1L, 3L, 3L, 2L, 4L, 4L, 4L,
3L, 4L, 4L, 4L, 1L, 4L, 1L, 1L, 4L, 3L, 4L, 4L, 1L, 1L, 4L, 3L,
4L, 2L, 1L, 2L, 2L, 4L, 2L, 2L, 3L), v7 = c(4L, 2L, 1L, 1L, 2L,
1L, 1L, 2L, 3L, 2L, 2L, 2L, 1L, 3L, 1L, 1L, 3L, 3L, 1L, 3L, 1L,
3L, 2L, 4L, 2L, 4L, 3L, 4L, 4L, 3L, 3L, 4L, 4L, 2L, 1L, 3L, 1L,
3L, 4L, 1L, 1L, 2L, 3L, 1L, 1L, 1L, 2L, 4L, 3L, 4L, 3L, 4L, 3L,
1L, 4L, 2L, 1L, 2L, 4L, 1L, 4L, 3L, 1L, 3L, 2L, 1L, 3L, 1L, 1L,
2L, 3L, 3L, 2L, 1L, 3L, 1L, 4L, 1L, 3L, 3L, 2L, 3L, 1L, 4L, 3L,
3L, 4L, 3L, 4L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 1L, 1L, 2L, 3L, 1L,
2L, 2L, 3L, 1L, 2L, 1L, 4L, 1L, 2L, 4L, 3L, 3L, 3L, 2L, 4L, 4L,
2L, 1L, 1L, 4L, 3L, 2L, 4L, 1L, 3L, 3L, 1L, 3L, 1L, 1L, 3L, 4L,
1L, 1L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 4L, 1L, 1L, 2L, 1L, 2L, 1L,
3L, 1L, 1L, 4L, 3L, 3L, 1L, 1L, 2L, 3L, 1L, 3L, 1L, 4L, 4L, 3L,
2L, 1L, 1L, 2L, 4L, 2L, 2L, 1L, 3L, 4L, 3L, 4L, 2L, 3L, 1L, 3L,
1L, 2L, 2L, 2L, 3L, 3L, 4L, 3L, 2L, 4L, 3L, 1L, 2L, 3L, 2L, 2L,
2L, 2L, 3L, 4L, 4L, 1L, 3L, 4L, 1L, 1L, 3L, 3L, 3L, 3L, 1L, 3L,
3L, 2L, 2L, 4L, 1L, 4L, 2L, 3L, 1L, 4L, 4L, 1L, 3L, 2L, 1L, 2L,
3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 3L, 3L, 4L, 2L, 4L, 4L, 3L,
3L, 4L, 2L, 2L, 4L, 3L, 1L, 4L, 3L, 1L, 1L, 1L, 1L, 1L, 4L, 4L,
1L, 1L, 3L, 4L, 4L, 3L, 1L, 2L, 4L, 1L, 3L, 1L, 1L, 1L, 4L, 3L,
1L, 4L, 1L, 4L, 3L, 3L, 2L, 3L, 3L, 1L, 1L, 2L, 1L, 2L, 1L, 2L,
4L, 3L, 4L, 2L, 1L, 2L, 1L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 4L, 3L,
2L, 2L, 1L, 1L, 1L, 4L, 1L, 2L, 4L, 2L, 4L, 1L, 4L, 4L, 1L, 4L,
3L, 1L, 2L, 2L, 4L, 2L, 3L, 4L, 1L, 3L, 4L, 4L, 1L, 2L, 4L, 1L,
3L, 4L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 4L, 4L, 4L, 1L, 4L, 1L, 2L,
2L, 2L, 1L, 2L, 3L, 4L, 4L, 2L, 3L, 4L, 4L, 2L, 2L, 4L, 4L, 4L,
2L, 3L, 3L, 3L, 2L, 2L, 4L, 4L, 2L, 1L, 3L, 3L, 2L, 3L, 1L, 2L,
1L, 1L, 1L, 3L, 2L, 4L, 1L, 1L, 3L, 1L, 4L, 1L, 4L, 1L, 3L, 2L,
3L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 4L, 3L, 4L, 1L, 3L, 1L, 3L, 2L,
4L, 1L, 3L, 3L, 3L, 3L, 4L, 1L, 1L, 3L, 3L, 1L, 4L, 3L, 2L, 1L,
3L, 3L, 1L, 4L, 3L, 4L, 2L, 2L, 3L, 4L, 4L, 4L, 2L, 1L, 3L, 2L,
2L, 4L, 3L, 1L, 2L, 3L, 1L, 1L, 1L, 3L, 2L, 4L, 1L, 4L, 1L, 2L,
3L, 2L, 1L, 4L, 3L, 4L, 3L, 3L, 1L, 4L, 1L, 4L, 1L, 1L, 3L, 4L,
1L, 4L, 1L, 2L, 3L, 4L, 4L, 1L, 2L, 1L, 3L, 3L, 4L, 3L, 1L),
v8 = c(4L, 1L, 2L, 3L, 4L, 1L, 3L, 3L, 1L, 2L, 2L, 2L, 1L,
3L, 1L, 1L, 4L, 4L, 2L, 4L, 2L, 1L, 1L, 3L, 2L, 3L, 4L, 3L,
4L, 1L, 3L, 3L, 3L, 1L, 2L, 4L, 4L, 1L, 1L, 1L, 2L, 1L, 3L,
1L, 3L, 1L, 3L, 4L, 3L, 4L, 1L, 3L, 4L, 1L, 3L, 1L, 1L, 2L,
4L, 4L, 3L, 3L, 4L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 4L, 4L, 2L,
3L, 4L, 1L, 2L, 1L, 3L, 3L, 1L, 3L, 2L, 4L, 2L, 1L, 3L, 3L,
4L, 3L, 3L, 4L, 3L, 4L, 1L, 3L, 1L, 2L, 1L, 2L, 2L, 1L, 2L,
1L, 3L, 1L, 1L, 4L, 1L, 2L, 4L, 3L, 3L, 3L, 1L, 1L, 4L, 1L,
3L, 1L, 3L, 3L, 1L, 4L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L,
4L, 2L, 1L, 3L, 3L, 4L, 1L, 4L, 2L, 1L, 1L, 2L, 2L, 4L, 3L,
2L, 4L, 1L, 1L, 1L, 4L, 3L, 1L, 3L, 2L, 3L, 1L, 3L, 1L, 3L,
3L, 3L, 1L, 2L, 2L, 4L, 3L, 1L, 4L, 1L, 3L, 3L, 4L, 1L, 1L,
2L, 2L, 4L, 2L, 3L, 1L, 1L, 3L, 3L, 3L, 4L, 2L, 3L, 2L, 4L,
1L, 3L, 2L, 1L, 1L, 1L, 4L, 4L, 4L, 1L, 4L, 4L, 2L, 1L, 3L,
3L, 3L, 4L, 1L, 1L, 4L, 2L, 2L, 3L, 3L, 1L, 1L, 4L, 1L, 4L,
4L, 3L, 3L, 2L, 4L, 1L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 4L, 2L,
3L, 3L, 4L, 2L, 1L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 4L, 1L, 1L,
3L, 2L, 1L, 1L, 2L, 3L, 4L, 3L, 1L, 2L, 3L, 3L, 4L, 1L, 1L,
4L, 2L, 1L, 2L, 1L, 4L, 2L, 2L, 4L, 2L, 4L, 2L, 3L, 3L, 3L,
1L, 4L, 3L, 2L, 2L, 1L, 2L, 4L, 1L, 2L, 3L, 1L, 3L, 1L, 2L,
3L, 1L, 1L, 1L, 3L, 3L, 2L, 1L, 1L, 3L, 3L, 2L, 1L, 1L, 1L,
3L, 3L, 3L, 1L, 3L, 3L, 3L, 1L, 2L, 3L, 1L, 3L, 3L, 1L, 1L,
1L, 4L, 1L, 4L, 1L, 1L, 2L, 3L, 4L, 3L, 2L, 4L, 1L, 4L, 3L,
1L, 3L, 4L, 1L, 4L, 3L, 2L, 4L, 4L, 4L, 1L, 4L, 1L, 2L, 1L,
2L, 2L, 2L, 3L, 2L, 4L, 3L, 3L, 3L, 4L, 3L, 1L, 4L, 3L, 4L,
1L, 4L, 3L, 3L, 1L, 4L, 3L, 2L, 1L, 4L, 3L, 3L, 1L, 4L, 2L,
1L, 2L, 1L, 2L, 4L, 2L, 3L, 4L, 3L, 1L, 4L, 4L, 1L, 3L, 2L,
4L, 1L, 3L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 4L, 3L, 4L, 1L, 3L,
2L, 3L, 4L, 3L, 2L, 3L, 4L, 3L, 1L, 4L, 1L, 1L, 4L, 4L, 1L,
3L, 3L, 2L, 1L, 3L, 3L, 1L, 3L, 3L, 1L, 4L, 1L, 3L, 4L, 4L,
2L, 1L, 3L, 3L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 2L, 1L, 1L, 4L,
1L, 3L, 1L, 4L, 2L, 2L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 3L, 1L,
3L, 1L, 4L, 2L, 3L, 3L, 4L, 2L, 3L, 3L, 1L, 3L, 3L, 3L, 1L,
1L, 3L, 4L, 4L, 4L, 3L, 1L), v9 = c(3L, 3L, 2L, 2L, 1L, 1L,
1L, 4L, 4L, 2L, 1L, 2L, 1L, 3L, 1L, 1L, 3L, 2L, 3L, 4L, 2L,
2L, 2L, 4L, 2L, 4L, 3L, 4L, 2L, 1L, 4L, 3L, 3L, 1L, 2L, 4L,
2L, 1L, 4L, 1L, 1L, 1L, 3L, 1L, 4L, 2L, 1L, 4L, 3L, 3L, 3L,
4L, 4L, 4L, 3L, 2L, 1L, 1L, 4L, 1L, 3L, 3L, 4L, 3L, 2L, 1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 2L, 3L, 1L, 1L, 1L, 3L, 3L, 2L,
4L, 1L, 1L, 4L, 1L, 1L, 3L, 4L, 3L, 3L, 4L, 3L, 4L, 1L, 3L,
2L, 1L, 2L, 1L, 2L, 2L, 1L, 3L, 2L, 4L, 1L, 1L, 2L, 4L, 3L,
4L, 3L, 3L, 1L, 4L, 4L, 1L, 4L, 2L, 4L, 2L, 2L, 4L, 4L, 3L,
3L, 4L, 3L, 1L, 2L, 4L, 4L, 3L, 2L, 2L, 3L, 1L, 3L, 2L, 4L,
1L, 4L, 1L, 2L, 2L, 3L, 2L, 4L, 2L, 2L, 1L, 2L, 4L, 3L, 1L,
3L, 1L, 3L, 3L, 4L, 1L, 3L, 4L, 3L, 1L, 1L, 3L, 1L, 3L, 1L,
1L, 1L, 3L, 4L, 3L, 2L, 1L, 4L, 2L, 3L, 2L, 1L, 1L, 1L, 4L,
4L, 4L, 3L, 2L, 3L, 2L, 4L, 2L, 3L, 2L, 1L, 2L, 1L, 3L, 3L,
3L, 1L, 3L, 4L, 1L, 1L, 4L, 3L, 3L, 3L, 2L, 3L, 4L, 1L, 2L,
3L, 1L, 1L, 4L, 4L, 1L, 4L, 4L, 2L, 3L, 2L, 1L, 1L, 3L, 3L,
3L, 1L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 4L, 1L, 1L, 3L, 3L, 4L,
3L, 2L, 2L, 4L, 3L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 4L, 1L,
2L, 1L, 3L, 3L, 4L, 3L, 2L, 1L, 1L, 1L, 4L, 4L, 4L, 2L, 3L,
4L, 2L, 3L, 2L, 1L, 4L, 3L, 1L, 3L, 3L, 2L, 1L, 1L, 2L, 2L,
1L, 1L, 4L, 1L, 3L, 2L, 1L, 2L, 2L, 3L, 1L, 3L, 3L, 2L, 1L,
1L, 3L, 4L, 1L, 1L, 2L, 1L, 1L, 4L, 2L, 2L, 2L, 1L, 3L, 1L,
4L, 2L, 1L, 3L, 3L, 2L, 1L, 1L, 1L, 1L, 4L, 1L, 1L, 2L, 3L,
3L, 3L, 1L, 4L, 4L, 3L, 3L, 1L, 3L, 2L, 4L, 4L, 3L, 4L, 3L,
3L, 4L, 2L, 3L, 3L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 3L, 4L,
3L, 4L, 1L, 2L, 4L, 4L, 3L, 1L, 3L, 4L, 3L, 1L, 1L, 3L, 4L,
1L, 4L, 4L, 4L, 1L, 3L, 2L, 2L, 2L, 1L, 2L, 3L, 1L, 1L, 3L,
3L, 2L, 3L, 3L, 4L, 1L, 3L, 4L, 1L, 3L, 1L, 2L, 2L, 1L, 1L,
2L, 1L, 1L, 1L, 4L, 1L, 3L, 1L, 4L, 1L, 4L, 2L, 3L, 3L, 3L,
3L, 4L, 2L, 1L, 4L, 4L, 1L, 4L, 4L, 1L, 2L, 3L, 3L, 1L, 4L,
3L, 2L, 2L, 1L, 3L, 3L, 3L, 1L, 2L, 2L, 4L, 1L, 2L, 4L, 3L,
2L, 1L, 3L, 1L, 1L, 1L, 3L, 4L, 2L, 1L, 3L, 1L, 1L, 4L, 2L,
2L, 3L, 4L, 3L, 3L, 4L, 1L, 3L, 1L, 4L, 2L, 3L, 3L, 1L, 2L,
1L, 3L, 2L, 3L, 3L, 3L, 2L, 1L, 1L, 4L, 3L, 3L, 4L, 2L)), .Names = c("v1",
"v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9"), row.names = c(NA,
-500L), class = "data.frame")
# simulation code
#-------------------------------------------------------------------------------------
# # load packages
# require(MultiOrd)
# require(parallel) # use the parallel package to speed runs
# # instantiate a (local) cluster with the number of cores from the options
# # and if the options are not set, detect the number of physical (not logical) cores
# cl <- makeCluster(getOption("cl.cores", detectCores(logical=FALSE)))
# # create input matrices
# ordPmat1 = matrix(cbind(.1,.4,.4,.1, # prob of option 1, 2, 3, 4
# .1,.4,.4,.1, # should add to 1 across
# .1,.4,.4,.1, # 9 of these, so 9 variables
# .2,.2,.2,.4,
# .2,.2,.2,.4,
# .2,.2,.2,.4,
# .3,.2,.3,.2,
# .3,.2,.3,.2,
# .3,.2,.3,.2
# ),nrow=4)
# cmat1= matrix(cbind(1,.5,.5,.4,.2,.2,.2,.2,.2, # all variables correlated
# .5,1,.5,.4,.2,.2,.2,.2,.2, # trying to get 3 factors
# .5,.5,1,.4,.2,.2,.2,.2,.2, # and 2 cross-loadings
# .4,.4,.4,1,.5,.5,.4,.2,.2,
# .2,.2,.2,.5,1,.5,.4,.2,.2,
# .2,.2,.2,.5,.5,1,.4,.2,.2,
# .2,.2,.2,.4,.4,.4,1,.5,.5,
# .2,.2,.2,.2,.2,.2,.5,1,.5,
# .2,.2,.2,.2,.2,.2,.5,.5,1
# ),nrow=9)
# # export the matrices to each instance of R on the cluster
# clusterExport(cl, c("ordPmat1", "cmat1"))
# # on each instance of R on the cluster, load the MultiOrd package
# clusterEvalQ(cl, require(MultiOrd))
# # Overriding simBinCorr function.
# simBinCorr<-function(ordPmat, CorrMat, nSim, steps=0.025){
#
# conformity.Check(ordPmat, CorrMat)
# p=find.binary.prob(ordPmat) # range of p is checked here
# pvec=p$p
#
# Mlocation=p$Mlocation
# del.next=CorrMat
# change=matrix(1, nrow(CorrMat), ncol(CorrMat) )
# iteration=0
# cat("calculating the intermediate binary correlations. \n");
#
# while ( sum(change>0.001) >0) {
# iteration=iteration+1
# ep0 = generate.binary( nSim, pvec, del.next)
# Mydata= BinToOrd(pvec, ordPmat, Mlocation, ep0)
# if (iteration<30){del.next[change>0.0001] = del.next[change>0.0001] + ( CorrMat[change>0.0001] - Mydata$Corr[change>0.0001] )*0.9 }
# else if(iteration<100){del.next[change>0.0001] = del.next[change>0.0001] + ( CorrMat[change>0.0001] - Mydata$Corr[change>0.0001] )*0.5 }
# else {del.next[change>0.0001] = del.next[change>0.0001] + ( CorrMat[change>0.0001] - Mydata$Corr[change>0.0001] )*0.1 }
#
# change[change>0.0001] = abs(CorrMat[change>0.0001] - Mydata$Corr[change>0.0001] )
# if(iteration%%40==0){cat("\n")}
# }
# cat("\n required ", iteration, " iterations to calculate intermediate binary correlations. \n");
# return(list(del.next=del.next, Mlocation=Mlocation, pvec=pvec) )
# }
#
# binObj <- simBinCorr(ordPmat1, cmat1, nSim=100000, steps=0.025)
# mydata = genOrd( 500, ordPmat1, binObj)
# # stop cluster
# stopCluster(cl)
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