forecasting. The parameter space for SSOE models may be specified to match that of the corresponding ARIMA scheme, or it may be … that underlies the Holt-Winters forecasting method. Conditionally heteroscedastic models may be developed in a similar …

to be forecast. The EIC provides a data-driven model selection tool that can be tuned to the particular forecasting task …'s Bayesian Information Criterion (BIC). The comparisons show that for the M3 forecasting competition data, the EIC outperforms …

the other periods. Croston's method is a widely used procedure for intermittent demand forecasting. However, it is an ad …

assumed to be Gaussian, the resulting prediction distribution may have an infinite variance beyond a certain forecasting … approximation causes no serious problems for parameter estimation or for forecasting one or two steps ahead. However, for longer …. The performance of the Gaussian approximation is compared with those of two lognormal models for short-term forecasting …

-term forecasting and also produce sensible long-term forecasts. The forecasts are compared with the official Australian government …

The application of traditional forecasting methods to discrete count data yields forecasts that are non-coherent. That …

We evaluate the performance of various methods for forecasting tourism demand. The data used include 380 monthly series … forecasting studies. The forecasting methods implemented in the competition are univariate time series approaches, and also … econometric models. This forecasting completion differs from previous competitions in several ways: (i) we concentrate only on …

Institute of Forecasters (Journal of Forecasting 1982-1985; International Journal of Forecasting 1985-2005). During this period …, over one third of all papers published in these journals concerned time series forecasting. We also review highly … influential works on time series forecasting that have been published elsewhere during this period. Enormous progress has been …

-validation (CV). However, when it comes to time series forecasting, because of the inherent serial correlation and potential non …) evaluation. In this paper, we show that the particular setup in which time series forecasting is usually performed using Machine …