Statistical Testing in Forecasting Model Selection

An expert system for forecasting model selection, written in Turbo-Prolog and implemented on a PC 386, allows a nonexpert in the forecasting field to utilize the relevant knowledge and use it to choose appropriate forecasting techniques. Detailed…

The literature has shown that no one model provides the most accurate forecasts. The focus has instead shifted to identifying the characteristics of the time series in order to provide guidelines for choosing the most appropriate extrapolation…

This paper presents a study on the impact of forecasting model selection on the value of information sharing in a supply chain with one capacitated supplier and multiple retailers. Using a computer simulation model, this study examines demand…

Applications of exponential smoothing to forecasting time series usually rely on three basic methods: simple exponential smoothing, trend corrected exponential smoothing and a seasonal variation thereof. A common approach to selecting the method…

A version of the state-of-the-art Weather Research and Forecasting model (WRF) has been developed for polar applications. The model known as "Polar WRF'' is tested over the Arctic Ocean with a western Arctic grid using 25-km resolution. The model is…

This paper focuses on the introduction of time durations to Model Based Statistical Testing. The concepts presented allow specifying durations of inputs and outputs within the test model. Three basic time restrictions are introduced: A stimulus must…

The paper identifies 29 models that the literature suggests are appropriate for technological forecasting. These models are divided into three classes according to the timing of the point of inflexion in the innovation or substitution process. Faced…

In this paper we present a novel methodology for estimating harmonic models in time series. The amplitude density function is derived from an inversion of the spectral representation of the series and is found to have the property of strong…

An analysis is presented of the requirements for developing a practical trainable classifier to detect and identify faults in vehicle powertrain systems. An examination is made of requirements on the data sets used for training and testing and the…

Many important questions in neuroscience are about interactions between neurons or neuronal groups. These interactions are often quantified by coherence, which is a frequency-indexed measure that quantifies the extent to which two signals exhibit a…