This paper uses linear and nonlinear statistical models, including artificial neural network (ANN) methods, to investigate the influence of the four economic factors, which are the national income (NI), population (POP), gross of domestic production (GDP), and consumer price index (CPI) on the...

The aim of this paper seeks to analyse how the energy price's cojuntural behaviour and structural conditions affect the short-run and mid-run overview of the energy integration process in South America (SA). For these porpoise we - first describe the world-wide energy agenda and the effect of...

The Commonwealth of Virginia abolished parole and reformed sentencing for all felony of-fenders committed on or after January 1, 1995. We examine the impact of this legislationon reported crime rates using different time series approaches. In particular, structuraltime series models are...

Our starting place is the first order seasonal autoregressive model. Its series are shown to have canonical model-based decompositions whose finite-sample estimates, filters, and error covariances have simple revealing formulas from basic linear regression.We obtain analogous formulas for...

The majority of classic SPC methodologies assume a steady-state (i.e., static) process behavior (i.e., the process mean and variance are constant) without the influence of the dynamic behavior (i.e., an intended or unintended shift in the process mean or variance). Traditional SPC has been...

Forecasting price spikes is a timely issue for the deregulated electricity market. Traditional price forecasting techniques show poor performance in handling price spikes, which usually follow a pattern different from the prices under normal market conditions. Therefore, novel approaches are...