Add Multiplicative Models/Seasonals #178.

Compute AR/Keras/Intermittent/Scikit models residues
antoinecarme · Mar 5, 2022 · 94cd00b · 94cd00b
1 parent 9703650
commit 94cd00b
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Showing 3 changed files with 6 additions and 9 deletions.
diff --git a/pyaf/TS/Intermittent_Models.py b/pyaf/TS/Intermittent_Models.py
@@ -131,7 +131,7 @@ def fit(self):
 
         lPredicted = self.croston(self.mARFrame);
         self.mARFrame[self.mOutName] = lPredicted['forecast']
-        self.mARFrame[self.mOutName + '_residue'] =  self.mARFrame[series] - self.mARFrame[self.mOutName]
+        self.compute_ar_residue(self.mARFrame)
 
         # print("ESTIMATE_CROSTON_MODEL_END" , self.mOutName);
 
@@ -140,7 +140,6 @@ def transformDataset(self, df, horizon_index = 1):
         series = self.mCycleResidueName;
         pred = self.croston(df, horizon_index)
         df[self.mOutName] = pred['forecast'];
-        target = df[series].values
-        df[self.mOutName + '_residue'] = target - df[self.mOutName].values        
+        self.compute_ar_residue(df)
         return df;
 
diff --git a/pyaf/TS/Keras_Models.py b/pyaf/TS/Keras_Models.py
@@ -91,7 +91,7 @@ def fit(self):
 
         # print("ESTIMATE_RNN_MODEL_STEP8" , self.mOutName);
 
-        self.mARFrame[self.mOutName + '_residue'] =  self.mARFrame[series] - self.mARFrame[self.mOutName]
+        self.compute_ar_residue(self.mARFrame)
 
         # print("ESTIMATE_RNN_MODEL_END" , self.mOutName, self.mModel.__dict__);
         # self.testPickle_old();
@@ -114,8 +114,7 @@ def transformDataset(self, df, horizon_index = 1):
         lPredicted = self.mModel.predict(inputs)
         lPredicted = np.reshape(lPredicted, (lPredicted.shape[0]))
         df[self.mOutName] = lPredicted;
-        target = df[series].values
-        df[self.mOutName + '_residue'] = target - df[self.mOutName].values        
+        self.compute_ar_residue(df)
         return df;
 
 class cMLP_Model(cAbstract_RNN_Model):

diff --git a/pyaf/TS/Scikit_Models.py b/pyaf/TS/Scikit_Models.py
@@ -106,7 +106,7 @@ def fit(self):
             # issue_34 failure SVD does not converge
             self.mARFrame[self.mOutName] = self.mDefaultValues[series]
 
-        self.mARFrame[self.mOutName + '_residue'] =  self.mARFrame[series] - self.mARFrame[self.mOutName]
+        self.compute_ar_residue(self.mARFrame)
 
         # print("ESTIMATE_SCIKIT_MODEL_END" , self.mOutName);
 
@@ -132,8 +132,7 @@ def transformDataset(self, df, horizon_index = 1):
         else:
             df[self.mOutName] = self.mDefaultValues[series];
 
-        target = df[series].values
-        df[self.mOutName + '_residue'] = target - df[self.mOutName].values        
+        self.compute_ar_residue(df)
         return df;