SARIMAX for demand forecasting
The code below runs SARIMAX to predict product demand by customer. First, the product types by customer are considered as a single combination, and then STL decomposition is performed on each combination, and the residuals from the decomposition results are used as dependent variables. Next, various variables are used as explanatory variables to run SARIMAX, and finally, the final demand is generated by multiplying the SARIMAX results by seasonality and trend. However, when I do this, the predicted value is set to be significantly higher than the actual value. Is there something wrong with the code? The data is normal, and there are no particular outliers
SARIMAX for demand forecasting
The code below runs SARIMAX to predict product demand by customer. First, the product types by customer are considered as a single combination, and then STL decomposition is performed on each combination, and the residuals from the decomposition results are used as dependent variables. Next, various variables are used as explanatory variables to run SARIMAX, and finally, the final demand is generated by multiplying the SARIMAX results by seasonality and trend. However, when I do this, the predicted value is set to be significantly higher than the actual value. Is there something wrong with the code? The data is normal, and there are no particular outliers
SARIMAX for demand forecasting
The code below runs SARIMAX to predict product demand by customer. First, the product types by customer are considered as a single combination, and then STL decomposition is performed on each combination, and the residuals from the decomposition results are used as dependent variables. Next, various variables are used as explanatory variables to run SARIMAX, and finally, the final demand is generated by multiplying the SARIMAX results by seasonality and trend. However, when I do this, the predicted value is set to be significantly higher than the actual value. Is there something wrong with the code? The data is normal, and there are no particular outliers
SARIMAX for demand forecasting
The code below runs SARIMAX to predict product demand by customer. First, the product types by customer are considered as a single combination, and then STL decomposition is performed on each combination, and the residuals from the decomposition results are used as dependent variables. Next, various variables are used as explanatory variables to run SARIMAX, and finally, the final demand is generated by multiplying the SARIMAX results by seasonality and trend. However, when I do this, the predicted value is set to be significantly higher than the actual value. Is there something wrong with the code? The data is normal, and there are no particular outliers
SARIMAX for demand forecasting
The code below runs SARIMAX to predict product demand by customer. First, the product types by customer are considered as a single combination, and then STL decomposition is performed on each combination, and the residuals from the decomposition results are used as dependent variables. Next, various variables are used as explanatory variables to run SARIMAX, and finally, the final demand is generated by multiplying the SARIMAX results by seasonality and trend. However, when I do this, the predicted value is set to be significantly higher than the actual value. Is there something wrong with the code? The data is normal, and there are no particular outliers