## Generate a 4-dim. sample with 2 latent classes of 500 data points each.
## The probabilities for the 2 classes are given by type1 and type2.
type1 <- c(0.8, 0.8, 0.2, 0.2)
type2 <- c(0.2, 0.2, 0.8, 0.8)
x <- matrix(runif(4000), nrow = 1000)
x[1:500,] <- t(t(x[1:500,]) < type1) * 1
x[501:1000,] <- t(t(x[501:1000,]) < type2) * 1
l <- lca(x, 2, niter=5)
print(l)
summary(l)
p <- predict(l, x)
table(p, c(rep(1,500),rep(2,500)))
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