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## Simulate toy data, n = 300 observations
set.seed(12345)
countmat <- matrix(runif(300*4, min=0, max=500), nrow=300, ncol=4)
countmat <- countmat[which(rowSums(countmat) > 0),]
conds <- rep(c("A","B","C","D"), each=2)
## Run the Normal mixture model for K = 2,3,4
run_arcsin <- coseq(y=countmat, K=2:4, iter=5, transformation="arcsin")
## Plot and summarize results
plot(run_arcsin)
summary(run_arcsin)
## Compare ARI values for all models (no plot generated here)
ARI <- compareARI(run_arcsin, plot=FALSE)
## Compare ICL values for models with arcsin and logit transformations
run_logit <- coseq(y=countmat, K=2:4, iter=5, transformation="logit")
compareICL(list(run_arcsin, run_logit))
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