From: Benjamin Goehry Date: Thu, 2 Feb 2017 13:18:54 +0000 (+0100) Subject: correction emgrank.R X-Git-Url: https://git.auder.net/variants/Chakart/img/doc/pieces/app_dev.php?a=commitdiff_plain;h=c3b2c1ab166494627b3b41f309fd747e1df61aa2;p=valse.git correction emgrank.R --- diff --git a/src/test/generate_test_data/helpers/EMGrank.R b/src/test/generate_test_data/helpers/EMGrank.R index 0ee2d1f..e34e0be 100644 --- a/src/test/generate_test_data/helpers/EMGrank.R +++ b/src/test/generate_test_data/helpers/EMGrank.R @@ -1,4 +1,6 @@ -EMGLLF = function(Pi, Rho, mini, maxi, X, Y, tau, rank){ +source("/home/goehry/Documents/valse/valse/R/vec_bin.R") +require(MASS) +EMGrank = function(Pi, Rho, mini, maxi, X, Y, tau, rank){ #matrix dimensions n = dim(X)[1] p = dim(X)[2] @@ -29,11 +31,21 @@ EMGLLF = function(Pi, Rho, mini, maxi, X, Y, tau, rank){ next } #U,S,V = SVD of (t(Xr)Xr)^{-1} * t(Xr) * Yr - [U,S,V] = svd(ginv(crossprod(X[Z_indice,]))%*% (X[Z_indice,])%*%Y[Z_indice,] ) + sv = svd(ginv( crossprod(X[Z_indice,]) ) %*% crossprod(X[Z_indice,], Y[Z_indice,]) ) + S = diag(sv$d) + U = sv$u + V = sv$v #Set m-rank(r) singular values to zero, and recompose #best rank(r) approximation of the initial product - S[rank(r)+1:end,] = 0 - phi[,,r] = U %*%S%*%t(V)%*%Rho[,,r] + if(r==k){ + j_r_1 = length(S) + } + else{ + j_r_1 = c(rank[r]+1:length(S)) + } + S[j_r_1] = 0 + S = diag(S, nrow = ncol(U)) + phi[,,r] = U %*% S %*% t(V) %*% Rho[,,r] } #Etape E et calcul de LLF @@ -59,7 +71,8 @@ EMGLLF = function(Pi, Rho, mini, maxi, X, Y, tau, rank){ #update distance parameter to check algorithm convergence (delta(phi, Phi)) deltaPhi = c(deltaPhi, max(max(max((abs(phi-Phi))/(1+abs(phi))))) ) if(length(deltaPhi) > deltaPhiBufferSize){ - deltaPhi = deltaPhi[2:length(deltaPhi)] + l_1 = c(2:length(deltaPhi)) + deltaPhi = deltaPhi[l_1] } sumDeltaPhi = sum(abs(deltaPhi))