Electricity price forecasting is becoming more important in everyday business of power utilities. Good forecasting models can increase effectiveness of producers and buyers playing roles in electricity market. Price is also a very important element in investment planning process. This paper presents a forecasting technique to model day-ahead spot price using well known ARIMA model to analyze an...

In this paper we develop a semi-parametric approach to model nonlinear relationships in serially correlated data. To illustrate the usefulness of this approach, we apply it to a set of hourly electricity load data. This approach takes into consideration the effect of temperature combined with those of timeof-day and type-of-day via nonparametric estimation. In addition, an ARIMA model is used t...

For the fractional ARIMA model, we demonstrate that wrong model speciication might lead to serious problems of inference in nite samples. We assess the performance of various model selection criteria when the true model is fractionally integrated and the alternatives of interest are ARMA and fractional ARIMA models. The likelihood of successful identiication increases substantially with rising ...

Both theoretical and empirical findings have suggested that combining different models can be an effective way to improve the predictive performance of each individual model. It is especially occurred when the models in the ensemble are quite different. Hybrid techniques that decompose a time series into its linear and nonlinear components are one of the most important kinds of the hybrid model...

Background: Any accident is a disturbance in the balance between the human system, vehicle, road and environment. Future prediction of traumatic accidents is a valuable factor for managers to make strategic decisions in the areas of safety, health and transportation. Materials and Methods: In this study, by using Grey Model (GM) (1.1), Rolling Grey Model (RGM), Fourier Grey Model (FGM) (1.1), ...

in this study, application of adaptive neuro-fuzzy inference system (anfis) in forecasting three perspectives (1, 2, and 4 years) ahead of iran’s agricultural products export was compared with arima as the most common econometrics linear forecasting method. for this purpose, iran’s agricultural products export revenues related to 1959-2010, and forecast performance measures such as r2, mad, and...

The paper constructs various core inflation measures. These include various trimmed means using disaggregated data and a structural VAR estimate of core inflation for Ireland. The ability of these core inflation measures to forecast future headline inflation is compared using a regression model. An ARIMA model fitted to the headline inflation rate is used as the benchmark forecast. The forecast...

This article explores an alternative state space representation for ARIMA models to that usually advocated. The alternative representation has minimal state order. More importantly, it has more convenient Kalman filter convergence properties. This convergence reveals the concrete connection between classical infinite sample representations based on lag polynomials and the recursive Kalman filte...