+++ /dev/null
-#' initialization of the EM algorithm
-#'
-#' @param k number of components
-#' @param X matrix of covariates (of size n*p)
-#' @param Y matrix of responses (of size n*m)
-#'
-#' @return a list with phiInit, rhoInit, piInit, gamInit
-#' @export
-#' @importFrom methods new
-#' @importFrom stats cutree dist hclust runif
-initSmallEM <- function(k, X, Y, fast = TRUE)
-{
- n <- nrow(Y)
- m <- ncol(Y)
- p <- ncol(X)
- nIte <- 20
- Zinit1 <- array(0, dim = c(n, nIte))
- betaInit1 <- array(0, dim = c(p, m, k, nIte))
- sigmaInit1 <- array(0, dim = c(m, m, k, nIte))
- phiInit1 <- array(0, dim = c(p, m, k, nIte))
- rhoInit1 <- array(0, dim = c(m, m, k, nIte))
- Gam <- matrix(0, n, k)
- piInit1 <- matrix(0, nIte, k)
- gamInit1 <- array(0, dim = c(n, k, nIte))
- LLFinit1 <- list()
-
- # require(MASS) #Moore-Penrose generalized inverse of matrix
- for (repet in 1:nIte)
- {
- distance_clus <- dist(cbind(X, Y))
- tree_hier <- hclust(distance_clus)
- Zinit1[, repet] <- cutree(tree_hier, k)
-
- for (r in 1:k)
- {
- Z <- Zinit1[, repet]
- Z_indice <- seq_len(n)[Z == r] #renvoit les indices où Z==r
- if (length(Z_indice) == 1) {
- betaInit1[, , r, repet] <- MASS::ginv(crossprod(t(X[Z_indice, ]))) %*%
- crossprod(t(X[Z_indice, ]), Y[Z_indice, ])
- } else {
- betaInit1[, , r, repet] <- MASS::ginv(crossprod(X[Z_indice, ])) %*%
- crossprod(X[Z_indice, ], Y[Z_indice, ])
- }
- sigmaInit1[, , r, repet] <- diag(m)
- phiInit1[, , r, repet] <- betaInit1[, , r, repet] #/ sigmaInit1[,,r,repet]
- rhoInit1[, , r, repet] <- solve(sigmaInit1[, , r, repet])
- piInit1[repet, r] <- mean(Z == r)
- }
-
- for (i in 1:n)
- {
- for (r in 1:k)
- {
- dotProduct <- tcrossprod(Y[i, ] %*% rhoInit1[, , r, repet]
- - X[i, ] %*% phiInit1[, , r, repet])
- Gam[i, r] <- piInit1[repet, r] *
- det(rhoInit1[, , r, repet]) * exp(-0.5 * dotProduct)
- }
- sumGamI <- sum(Gam[i, ])
- gamInit1[i, , repet] <- Gam[i, ]/sumGamI
- }
-
- miniInit <- 10
- maxiInit <- 11
-
- init_EMG <- EMGLLF(phiInit1[, , , repet], rhoInit1[, , , repet], piInit1[repet, ],
- gamInit1[, , repet], miniInit, maxiInit, gamma = 1, lambda = 0, X, Y,
- eps = 1e-04, fast)
- LLFEessai <- init_EMG$LLF
- LLFinit1[repet] <- LLFEessai[length(LLFEessai)]
- }
- b <- which.min(LLFinit1)
- phiInit <- phiInit1[, , , b]
- rhoInit <- rhoInit1[, , , b]
- piInit <- piInit1[b, ]
- gamInit <- gamInit1[, , b]
-
- return(list(phiInit = phiInit, rhoInit = rhoInit, piInit = piInit, gamInit = gamInit))
-}