R/class_topics_2.R

In kkdey/classtpx: MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.

### main classtpx function when a known theta matrix is provided by the user

class_topics_2 <- function(counts, 
                         K, 
                         theta_known, 
                         class_labs=NULL, 
                         method=c("omega.fix", "theta.fix", "theta.prior","no.fix"),
                         optional_theta=NULL,
                         shrink=TRUE,
                         shrink.method=c(1,2),
                         mash_user=NULL,
                         shape=NULL, 
                         initopics=NULL, 
                         tol=0.1, 
                         bf=FALSE, 
                         kill=2, 
                         ord=TRUE, verb=1, 
                         tmax=10000, wtol=10^(-4), 
                         qn=100, grp=NULL, admix=TRUE, 
                         prior_omega = NULL,
                         nonzero=FALSE, dcut=-10){
  
  
  K_classes <- dim(theta_known)[2]
  if(is.null(prior_omega)){
    prior_omega <- rep(1/K, K);
  }else{
    prior_omega <- (prior_omega/sum(prior_omega))
  }
  
  
}