X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FEMGrank.R;h=5eea322f6c47c677d843cca24205f0afea64c24a;hp=7c0d91f653a226a7b5bdf61f755eb2fee70af95c;hb=0930b5d395ef0a48d1f97f88ee533c13d0962759;hpb=7ac88d643dac3dccb17c3e81c7b3d3d1aa87c1af

diff --git a/pkg/R/EMGrank.R b/pkg/R/EMGrank.R
index 7c0d91f..5eea322 100644
--- a/pkg/R/EMGrank.R
+++ b/pkg/R/EMGrank.R
@@ -48,7 +48,6 @@ matricize <- function(X)
 # R version - slow but easy to read
 .EMGrank_R = function(Pi, Rho, mini, maxi, X, Y, tau, rank)
 {
-  require(MASS)
   #matrix dimensions
   n = dim(X)[1]
   p = dim(X)[2]
@@ -77,7 +76,7 @@ matricize <- function(X)
       if (length(Z_indice) == 0)
         next
       #U,S,V = SVD of (t(Xr)Xr)^{-1} * t(Xr) * Yr
-      s = svd( ginv(crossprod(matricize(X[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
@@ -107,7 +106,7 @@ matricize <- function(X)
 			}
 			sumLogLLF2 = sumLogLLF2 + log(sumLLF1)
 		}
-  
+
 		LLF = -1/n * sumLogLLF2
 
 		#update distance parameter to check algorithm convergence (delta(phi, Phi))