diff --git a/GPy/models/gp_coregionalized_regression.py b/GPy/models/gp_coregionalized_regression.py
index 66edb8d7..6604f634 100644
--- a/GPy/models/gp_coregionalized_regression.py
+++ b/GPy/models/gp_coregionalized_regression.py
@@ -38,7 +38,7 @@ class GPCoregionalizedRegression(GP):
         if kernel is None:
             kernel = kern.RBF(X.shape[1]-1)
             
-            kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=1,name=kernel_name)
+            kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=W_rank,name=kernel_name)
 
         #Likelihood
         likelihood = util.multioutput.build_likelihood(Y_list,self.output_index,likelihoods_list)
diff --git a/GPy/models/sparse_gp_coregionalized_regression.py b/GPy/models/sparse_gp_coregionalized_regression.py
index 88841891..2a19d52c 100644
--- a/GPy/models/sparse_gp_coregionalized_regression.py
+++ b/GPy/models/sparse_gp_coregionalized_regression.py
@@ -44,7 +44,7 @@ class SparseGPCoregionalizedRegression(SparseGP):
         if kernel is None:
             kernel = kern.RBF(X.shape[1]-1)
             
-            kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=1,name=kernel_name)
+            kernel = util.multioutput.ICM(input_dim=X.shape[1]-1, num_outputs=Ny, kernel=kernel, W_rank=W_rank, name=kernel_name)
 
         #Likelihood
         likelihood = util.multioutput.build_likelihood(Y_list,self.output_index,likelihoods_list)