Nothing
#' compute the Integrated likeilhood and the ICL criteria for the MBM
#'
#' @param paramEstim Estimated parameters of MBM
#' @param list_Net A list of network
#' @param v_distrib Type of proababilistic distributions in each network : if 0/1 then Bernoulli, if counting then Poisson. My default = Bernoulli.
#' Must give a vector whose length is the number of networks in list_Net
#' @return Pseudo-Likelihood and penalty
#'
#' @export
compLikICL <- function(paramEstim,list_Net,v_distrib = NULL)
{
dataR6 = formattingData(list_Net,v_distrib)
list_MaskNA <- lapply(dataR6$mats,function(m){1 * (1 - is.na(m))})
tau <- paramEstim$tau
list_pi <- paramEstim$list_pi
if (is.null(list_pi)) { list_pi <- lapply(tau,colMeans) }
list_theta <- paramEstim$list_theta
if (is.null(v_distrib)) {v_distrib <- paramEstim$v_distrib}
res <- compLikICLInt(tau,list_theta,list_pi,dataR6$Ecode,dataR6$mats,list_MaskNA,dataR6$v_NQ,paramEstim$v_K,v_distrib)
return(res)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.