diff --git a/PyCTBN/PyCTBN/parameters_estimator.py b/PyCTBN/PyCTBN/parameters_estimator.py
index 8b50a92..48355f7 100644
--- a/PyCTBN/PyCTBN/parameters_estimator.py
+++ b/PyCTBN/PyCTBN/parameters_estimator.py
@@ -17,11 +17,11 @@ class ParametersEstimator:
     :_single_set_of_cims: the set of cims object that will hold the cims of the node
     """
 
-    def __init__(self, times, trajectories, net_graph: NetworkGraph):
+    def __init__(self, net_graph: NetworkGraph):
         """Constructor Method
         """
-        self._times = times
-        self._trajectories = trajectories
+        #self._times = times
+        #self._trajectories = trajectories
         self._net_graph = net_graph
         self._single_set_of_cims = None
 
@@ -35,7 +35,7 @@ class ParametersEstimator:
         node_states_number = self._net_graph.get_states_number(node_id)
         self._single_set_of_cims = SetOfCims(node_id, p_vals, node_states_number, self._net_graph.p_combs)
 
-    def compute_parameters_for_node(self, node_id: str) -> SetOfCims:
+    def compute_parameters_for_node(self, node_id: str, times, trajectories) -> SetOfCims:
         """Compute the CIMS of the node identified by the label ``node_id``.
 
         :param node_id: the node label
@@ -46,20 +46,21 @@ class ParametersEstimator:
         node_indx = self._net_graph.get_node_indx(node_id)
         state_res_times = self._single_set_of_cims._state_residence_times
         transition_matrices = self._single_set_of_cims._transition_matrices
-        self.compute_state_res_time_for_node(node_indx, self._times,
-                                             self._trajectories,
+        self.compute_state_res_time_for_node(node_indx, times,
+                                             trajectories,
                                              self._net_graph.time_filtering,
                                              self._net_graph.time_scalar_indexing_strucure,
                                              state_res_times)
         self.compute_state_transitions_for_a_node(node_indx,
-                                                  self._trajectories,
+                                                  trajectories,
                                                   self._net_graph.transition_filtering,
                                                   self._net_graph.transition_scalar_indexing_structure,
                                                   transition_matrices)
         self._single_set_of_cims.build_cims(state_res_times, transition_matrices)
         return self._single_set_of_cims
 
-    def compute_state_res_time_for_node(self, node_indx: int, times: np.ndarray, trajectory: np.ndarray,
+    @staticmethod
+    def compute_state_res_time_for_node(node_indx: int, times: np.ndarray, trajectory: np.ndarray,
                                         cols_filter: np.ndarray, scalar_indexes_struct: np.ndarray,
                                         T: np.ndarray) -> None:
         """Compute the state residence times for a node and fill the matrix ``T`` with the results
@@ -82,7 +83,8 @@ class ParametersEstimator:
                            times,
                            minlength=scalar_indexes_struct[-1]).reshape(-1, T.shape[1])
 
-    def compute_state_transitions_for_a_node(self, node_indx: int, trajectory: np.ndarray, cols_filter: np.ndarray,
+    @staticmethod
+    def compute_state_transitions_for_a_node(node_indx: int, trajectory: np.ndarray, cols_filter: np.ndarray,
                                              scalar_indexing: np.ndarray, M: np.ndarray):
         """Compute the state residence times for a node and fill the matrices ``M`` with the results.
 
diff --git a/PyCTBN/PyCTBN/structure_estimator.py b/PyCTBN/PyCTBN/structure_estimator.py
index 7864d6d..18c87ed 100644
--- a/PyCTBN/PyCTBN/structure_estimator.py
+++ b/PyCTBN/PyCTBN/structure_estimator.py
@@ -124,9 +124,9 @@ class StructureEstimator:
             s1 = Structure(l1, indxs1, vals1, eds1, tot_vars_count)
             g1 = NetworkGraph(s1)
             g1.fast_init(test_child)
-            p1 = ParametersEstimator(self._times, self._trajectories, g1)
+            p1 = ParametersEstimator(g1)
             p1.fast_init(test_child)
-            sofc1 = p1.compute_parameters_for_node(test_child)
+            sofc1 = p1.compute_parameters_for_node(test_child, self._times, self._trajectories)
             cache.put(set(p_set), sofc1)
         sofc2 = None
         p_set.insert(0, test_parent)
@@ -142,9 +142,9 @@ class StructureEstimator:
             s2 = Structure(l2, indxs2, vals2, eds2, tot_vars_count)
             g2 = NetworkGraph(s2)
             g2.fast_init(test_child)
-            p2 = ParametersEstimator(self._times, self._trajectories, g2)
+            p2 = ParametersEstimator(g2)
             p2.fast_init(test_child)
-            sofc2 = p2.compute_parameters_for_node(test_child)
+            sofc2 = p2.compute_parameters_for_node(test_child, self._times, self._trajectories)
             cache.put(set(p_set), sofc2)
         for cim1, p_comb in zip(sofc1.actual_cims, sofc1.p_combs):
             cond_cims = sofc2.filter_cims_with_mask(cims_filter, p_comb)
@@ -204,7 +204,7 @@ class StructureEstimator:
         u = list(self._complete_graph.predecessors(var_id))
         #child_states_numb = self._sample_path.structure.get_states_number(var_id)
         child_states_numb = self._nodes_vals[np.where(self._nodes == var_id)][0]
-        print("Child States Numb", child_states_numb)
+        #print("Child States Numb", child_states_numb)
         b = 0
         while b < len(u):
             parent_indx = 0
@@ -221,7 +221,7 @@ class StructureEstimator:
                 if not removed:
                     parent_indx += 1
             b += 1
-        print("Parent set for node ", var_id, " : ", u)
+        #print("Parent set for node ", var_id, " : ", u)
         cache.clear()
         return u
 
@@ -251,7 +251,7 @@ class StructureEstimator:
         total_vars_numb_list = [self._tot_vars_number] * len(self._nodes)
         cpu_count = multiprocessing.cpu_count()
         print("CPU COUNT", cpu_count)
-        with multiprocessing.Pool(processes=cpu_count) as pool:
+        with multiprocessing.Pool(processes=1) as pool:
             parent_sets = pool.starmap(ctpc_algo, zip(self._nodes, self._caches, total_vars_numb_list))
         #parent_sets = [ctpc_algo(n, c, total_vars_numb) for n, c in tqdm(zip(self._nodes, self._caches))]
         print(parent_sets)