| Abstract [eng] |
The time series forecasting is widely applied in all over the world and in many various ranges. The main aim of this master‘s work – to compose the forecasting model of Kaunas municipal waste by using exogenous variables. According the data of 2000-2009 year was made prediction for two years forward. These forecasts was made by using four different forecasting models, those are: Autoregressive integrated moving average, Seasonal Dummy model was used with exogenous variables included, such as consumable goods and services price difference, unemployment level, minimal wage per hour. After many countings, analyses with statistical program SAS, and data researches was identified, that the best model for Kaunas municipal waste forecasting was Seasonal Dummy model was used with exogenous variables included, such as consumable goods and services price difference. This master‘s work might be useful in national projects to reduce the pollution or help to concentrate in forecasts which will help consider what new vacancies can be created to plan further moves to research and develope environmental-friendly questions. |
