diff --git a/pyFTS/models/hwang.py b/pyFTS/models/hwang.py
index 6f862d7..dbfb050 100644
--- a/pyFTS/models/hwang.py
+++ b/pyFTS/models/hwang.py
@@ -19,6 +19,10 @@ class HighOrderFTS(fts.FTS):
         self.detail = "Hwang"
 
     def forecast(self, ndata, **kwargs):
+        
+        if 'order' in kwargs:
+            self.order = kwargs.get('order',self.order)
+            self.max_lag = self.order
 
         if self.sets == None:
             self.sets = self.partitioner.sets
@@ -57,4 +61,4 @@ class HighOrderFTS(fts.FTS):
         return ret
 
     def train(self, data, **kwargs):
-        pass
\ No newline at end of file
+        pass
diff --git a/pyFTS/models/seasonal/cmsfts.py b/pyFTS/models/seasonal/cmsfts.py
index 45302cc..08d0e80 100644
--- a/pyFTS/models/seasonal/cmsfts.py
+++ b/pyFTS/models/seasonal/cmsfts.py
@@ -81,14 +81,18 @@ class ContextualMultiSeasonalFTS(sfts.SeasonalFTS):
         ndata = self.indexer.get_data(data)
 
         for k in np.arange(0, len(data)):
+            
+            if str(index[k]) in self.flrgs:
 
-            flrg = self.flrgs[str(index[k])]
+                flrg = self.flrgs[str(index[k])]
 
-            d = FuzzySet.get_fuzzysets(ndata[k], self.sets, ordered_sets, alpha_cut=self.alpha_cut)
+                d = FuzzySet.get_fuzzysets(ndata[k], self.sets, ordered_sets, alpha_cut=self.alpha_cut)
 
-            mp = self.get_midpoints(flrg, d)
+                mp = self.get_midpoints(flrg, d)
 
-            ret.append(sum(mp) / len(mp))
+                ret.append(sum(mp) / len(mp))
+            else:
+                ret.append(np.nan)
 
         return ret