The aim of this paper is the analysis of methodology for selecting the best model for forecasting of fuelwood demand in Greece for the years 2020, 2025 and 2030 with a final objective the decision-making in the sector...The aim of this paper is the analysis of methodology for selecting the best model for forecasting of fuelwood demand in Greece for the years 2020, 2025 and 2030 with a final objective the decision-making in the sector of forest bioenergy. A complete time series of historical data exists that concerns： （a） the consumption of fuelwood and （b） the six most important from the independent variables that could influence the consumption of fuelwood, whose data cover the time period 1989-2010. The evaluation and choice of the best model was realized with the help of the following six statistical criteria： （a） the size of standard error of theoretical values of dependant variable, S. E.; （b） the value of adjusted R square （R2）; （c） the non-existence of autocorrelation among the residuals （ei） through the criterion Durbin-Watson; （d） the statistical significance of models coefficients through t criterion; （e） the statistical significance of models through F criterion and （f） the non-existence of multicolinearity through the values of Variance Inflation Factor.展开更多
文摘The aim of this paper is the analysis of methodology for selecting the best model for forecasting of fuelwood demand in Greece for the years 2020, 2025 and 2030 with a final objective the decision-making in the sector of forest bioenergy. A complete time series of historical data exists that concerns： （a） the consumption of fuelwood and （b） the six most important from the independent variables that could influence the consumption of fuelwood, whose data cover the time period 1989-2010. The evaluation and choice of the best model was realized with the help of the following six statistical criteria： （a） the size of standard error of theoretical values of dependant variable, S. E.; （b） the value of adjusted R square （R2）; （c） the non-existence of autocorrelation among the residuals （ei） through the criterion Durbin-Watson; （d） the statistical significance of models coefficients through t criterion; （e） the statistical significance of models through F criterion and （f） the non-existence of multicolinearity through the values of Variance Inflation Factor.
