Commit | Line | Data |
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c3b2c1ab BG |
1 | require(MASS) |
2 | EMGrank = function(Pi, Rho, mini, maxi, X, Y, tau, rank){ | |
c2028869 BG |
3 | #matrix dimensions |
4 | n = dim(X)[1] | |
5 | p = dim(X)[2] | |
6 | m = dim(Rho)[2] | |
7 | k = dim(Rho)[3] | |
8 | ||
9 | #init outputs | |
10 | phi = array(0, dim=c(p,m,k)) | |
11 | Z = rep(1, n) | |
12 | Pi = piInit | |
13 | LLF = 0 | |
14 | ||
15 | #local variables | |
16 | Phi = array(0, dim=c(p,m,k)) | |
17 | deltaPhi = c(0) | |
18 | sumDeltaPhi = 0 | |
19 | deltaPhiBufferSize = 20 | |
20 | ||
21 | #main loop | |
22 | ite = 1 | |
23 | while(ite<=mini || (ite<=maxi && sumDeltaPhi>tau)){ | |
24 | #M step: Mise à jour de Beta (et donc phi) | |
25 | for(r in 1:k){ | |
9ade3f1b | 26 | Z_bin = valse:::vec_bin(Z,r) |
c2028869 BG |
27 | Z_vec = Z_bin$vec #vecteur 0 et 1 aux endroits o? Z==r |
28 | Z_indice = Z_bin$indice | |
29 | if(sum(Z_indice) == 0){ | |
30 | next | |
31 | } | |
32 | #U,S,V = SVD of (t(Xr)Xr)^{-1} * t(Xr) * Yr | |
c3b2c1ab BG |
33 | sv = svd(ginv( crossprod(X[Z_indice,]) ) %*% crossprod(X[Z_indice,], Y[Z_indice,]) ) |
34 | S = diag(sv$d) | |
35 | U = sv$u | |
36 | V = sv$v | |
c2028869 BG |
37 | #Set m-rank(r) singular values to zero, and recompose |
38 | #best rank(r) approximation of the initial product | |
c3b2c1ab BG |
39 | if(r==k){ |
40 | j_r_1 = length(S) | |
41 | } | |
42 | else{ | |
43 | j_r_1 = c(rank[r]+1:length(S)) | |
44 | } | |
45 | S[j_r_1] = 0 | |
46 | S = diag(S, nrow = ncol(U)) | |
47 | phi[,,r] = U %*% S %*% t(V) %*% Rho[,,r] | |
c2028869 BG |
48 | } |
49 | ||
50 | #Etape E et calcul de LLF | |
51 | sumLogLLF2 = 0 | |
52 | for(i in 1:n){ | |
53 | sumLLF1 = 0 | |
54 | maxLogGamIR = -Inf | |
55 | for(r in 1:k){ | |
56 | dotProduct = tcrossprod(Y[i,]%*%Rho[,,r]-X[i,]%*%phi[,,r]) | |
57 | logGamIR = log(Pi[r]) + log(det(Rho[,,r])) - 0.5*dotProduct | |
58 | #Z[i] = index of max (gam[i,]) | |
59 | if(logGamIR > maxLogGamIR){ | |
60 | Z[i] = r | |
61 | maxLogGamIR = logGamIR | |
62 | } | |
63 | sumLLF1 = sumLLF1 + exp(logGamIR) / (2*pi)^(m/2) | |
64 | } | |
65 | sumLogLLF2 = sumLogLLF2 + log(sumLLF1) | |
66 | } | |
67 | ||
68 | LLF = -1/n * sumLogLLF2 | |
69 | ||
70 | #update distance parameter to check algorithm convergence (delta(phi, Phi)) | |
71 | deltaPhi = c(deltaPhi, max(max(max((abs(phi-Phi))/(1+abs(phi))))) ) | |
72 | if(length(deltaPhi) > deltaPhiBufferSize){ | |
c3b2c1ab BG |
73 | l_1 = c(2:length(deltaPhi)) |
74 | deltaPhi = deltaPhi[l_1] | |
c2028869 BG |
75 | } |
76 | sumDeltaPhi = sum(abs(deltaPhi)) | |
77 | ||
78 | #update other local variables | |
79 | Phi = phi | |
80 | ite = ite+1 | |
81 | ||
82 | } | |
83 | return(list(phi=phi, LLF=LLF)) | |
9ade3f1b | 84 | } |