alphai:

In SaraTouzani/EM: Algorithme EM ("Espérance-Maximisation")

Usage

alphai(Y, Xquali)

Arguments

Y
Xquali

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (Y, Xquali) 
{
    Xquali_k <- as.list(unique(Y))
    if (is.null(dim(Xquali))) {
        j <- 1
        for (i in unique(Y)) {
            Xquali_k[[j]] <- data.frame(MAT = Xquali[Y == i])
            j <- j + 1
        }
        alpha_k <- as.list(unique(Y))
        for (k in 1:length(alpha_k)) {
            variables <- vector("list", 1)
            X <- as.numeric(table(Xquali_k[[k]])/nrow(Xquali_k[[k]]))
            variables[[1]] <- data.frame(proba = X, modalite = unlist(attributes(table(Xquali_k[[k]])/nrow(Xquali_k[[k]]))$dimnames))
            for (h in unique(Xquali)) {
                if (!(h %in% variables[[1]]$modalite)) {
                  mod_miss <- data.frame(proba = 0, modalite = h)
                  variables[[1]] <- rbind(variables[[1]], mod_miss)
                }
            }
            variables[[1]]$modalite <- as.character(variables[[1]]$modalite)
            variables[[1]] <- variables[[1]][order(variables[[1]]$modalite, 
                decreasing = F), ]
            alpha_k[[k]] <- variables
        }
    }
    else {
        j <- 1
        for (i in unique(Y)) {
            Xquali_k[[j]] <- data.frame(MAT = Xquali[Y == i, 
                ])
            j <- j + 1
        }
        alpha_k <- as.list(unique(Y))
        for (k in 1:length(alpha_k)) {
            variables <- as.list(colnames(Xquali))
            for (j in 1:length(variables)) {
                X <- as.numeric(table(Xquali_k[[k]][, j])/nrow(Xquali_k[[k]]))
                variables[[j]] <- data.frame(proba = X, Var = variables[[j]], 
                  modalite = unlist(attributes(table(Xquali_k[[k]][, 
                    j])/nrow(Xquali_k[[k]]))$dimnames))
                for (h in unique(Xquali[, j])) {
                  if (!(h %in% variables[[j]]$modalite)) {
                    mod_miss <- data.frame(proba = 0, Var = unique(variables[[j]]$Var), 
                      modalite = h)
                    variables[[j]] <- rbind(variables[[j]], mod_miss)
                  }
                }
                variables[[j]]$modalite <- as.character(variables[[j]]$modalite)
                variables[[j]] <- variables[[j]][order(variables[[j]]$modalite, 
                  decreasing = F), ]
            }
            alpha_k[[k]] <- variables
        }
    }
    return(alpha_k)
  }

SaraTouzani/EM documentation built on Dec. 16, 2019, 12:31 a.m.