R/fitMclust1D.R

In rretkute/AMISEpi: AMIS for Infectious Diseases

#' Fit clusters of mixtures foe 1D case
#'
#' AMIS.
#'
#' @param xx Sampled parameters
#' @param G Sequence of clusters
#' @return Parameters of mixture
#' @author Renata Retkute, \email{r.retkute@@yahoo.com}
#' @export
#'



fitMclust1D<-function(xx,modelName="V",G= G){
  
  options(warn=-1)
  
  control <- emControl(eps=sqrt(.Machine$double.eps))
  
  n <- length(xx)
  p <- 1
  
  clustering <-Gout <- BIC <- NA
  
  if (G[1] == 1) {
    clustering <- mvn(modelName = modelName, data = xx)
    BIC <- bic(modelName=modelName,loglik=clustering$loglik,n=n,d=p,G=1)
    Gout <- 1
    G <- G[-1]
  }
  
  hcPairs <- hc(modelName="V",data=xx)
  clss <- hclass(hcPairs, G)
  
  for (g in G) {
    
    cl <- clss[, as.character(g)]
    z <- unmap(cl, groups = 1:max(cl))
    
    new <- me(modelName=modelName,data=xx,z=z,control=control)
    
    if(!is.na(new$loglik)){
      
      BICnew <- bic(modelName=modelName,loglik=new$loglik,n=n,d=p,G=g,equalPro=control$equalPro)
      
      if(is.na(BIC)){
        clustering <- new
        BIC <- BICnew
        Gout <- g
      }else{
        if(BICnew>BIC){
          clustering <- new
          BIC <- BICnew
          Gout <- g
        }
      }
    }
  }
  
  options(warn=0)
  
  return(c(clustering,G=Gout))
  
}