fk2:

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

Usage

fk2(Xquanti, mean, sigma, Y, Xijh, alpha_k, K = length(sigma), n = nrow(Xquanti), p = length(colnames(Xquali)))

Arguments

Xquanti
mean
sigma
Y
Xijh
alpha_k
K
n
p

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 (Xquanti, mean, sigma, Y, Xijh, alpha_k, K = length(sigma), 
    n = nrow(Xquanti), p = length(colnames(Xquali))) 
{
    if (p == 0) {
        p <- 1
    }
    fk_quali_ik <- matrix(1, nrow = n, ncol = length(unique(Y)))
    K = length(unique(Y))
    for (i in 1:n) {
        for (k in 1:K) {
            for (j in 1:p) {
                fk_quali_ik[i, k] <- fk_quali_ik[i, k] * (as.numeric(alpha_k[[k]][[j]][["proba"]] %*% 
                  as.numeric(Xijh[[j]][i, -length(Xijh[[j]][i, 
                    ])])))
            }
        }
    }
    fk_quati_ik <- matrix(1, nrow = n, ncol = length(unique(Y)))
    p = length(colnames(Xquanti))
    if (p == 0) {
        p <- 1
    }
    for (i in 1:n) {
        for (k in 1:K) {
            fk_quati_ik[i, k] <- (1/(((2 * pi)^(p/2)) * (det(as.matrix(sigma[[k]]))^(0.5)))) * 
                exp((Xquanti[i, ] - as.numeric(mean[k, -1])) %*% 
                  ginv(as.matrix(sigma[[k]])) %*% as.matrix(Xquanti[i, 
                  ] - as.numeric(mean[k, -1])) * (-0.5))
        }
    }
    fkxi <- as.list(seq_len(nrow(Xquanti)))
    for (i in 1:n) {
        fkxi[[i]] <- data.frame(densite = fk_quali_ik[i, ] * 
            fk_quati_ik[i, ])
    }
    return(fkxi)
  }

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