- 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
-
- new_EMG = EMGLLF(phiInit1[,,,repet], rhoInit1[,,,repet], piInit1[repet,],
- gamInit1[,,repet], miniInit, maxiInit, gamma=1, lambda=0, X, Y, tau=1e-4)
- LLFEessai = new_EMG$LLF
- LLFinit1[repet] = LLFEessai[length(LLFEessai)]
- }
+ 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)
+ }