A Study on increasing the fitness of forecasts using Dynamic Model

동적 모형에 의한 예측치의 정도 향상에 관한 연구

We develop a dynamic demand forecasting model compared to regression analysis model and AutoRegressive Integrated Moving Average(ARIMA) model. The dynamic model can apply to the current dynamic data to forecasts through introducing state equation. A multiple regression model and ARIMA model using given data are designed via the model analysis. The forecasting fitness evaluation between the designed models and the dynamic model is compared with the criterion of sum of squared error.