X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FEMGrank.R;h=b85a0faf4fd9b1b2cea2c4f7b11ccf5c9371a08d;hp=db409481bcfffe6a94000d6982b18ce1f2ccedb1;hb=ea5860f1b4fc91f06e371a0b26915198474a849d;hpb=1b698c1619dbcf5b3a0608dc894d249945d2bce3 diff --git a/pkg/R/EMGrank.R b/pkg/R/EMGrank.R index db40948..b85a0fa 100644 --- a/pkg/R/EMGrank.R +++ b/pkg/R/EMGrank.R @@ -46,10 +46,10 @@ matricize <- function(X) .EMGrank_R <- function(Pi, Rho, mini, maxi, X, Y, tau, rank) { # matrix dimensions - n <- dim(X)[1] - p <- dim(X)[2] - m <- dim(Rho)[2] - k <- dim(Rho)[3] + n <- nrow(X) + p <- ncol(X) + m <- ncol(Y) + k <- length(Pi) # init outputs phi <- array(0, dim = c(p, m, k)) @@ -73,8 +73,8 @@ matricize <- function(X) if (length(Z_indice) == 0) next # U,S,V = SVD of (t(Xr)Xr)^{-1} * t(Xr) * Yr - s <- svd(MASS::ginv(crossprod(matricize(X[Z_indice, ]))) - %*% crossprod(matricize(X[Z_indice, ]), matricize(Y[Z_indice, ]))) + s <- svd(MASS::ginv(crossprod(matricize(X[Z_indice, ]))) %*% + crossprod(matricize(X[Z_indice, ]), matricize(Y[Z_indice, ]))) S <- s$d # Set m-rank(r) singular values to zero, and recompose best rank(r) approximation # of the initial product @@ -92,7 +92,7 @@ matricize <- function(X) for (r in seq_len(k)) { dotProduct <- tcrossprod(Y[i, ] %*% Rho[, , r] - X[i, ] %*% phi[, , r]) - logGamIR <- log(Pi[r]) + log(det(Rho[, , r])) - 0.5 * dotProduct + logGamIR <- log(Pi[r]) + log(gdet(Rho[, , r])) - 0.5 * dotProduct # Z[i] = index of max (gam[i,]) if (logGamIR > maxLogGamIR) {