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 …

exponential smoothing method of forecasting on a database of demand series for slow moving car parts. The methods considered … negative binomial measurements, and the Croston method of forecasting. In the case of the Croston method, a maximum likelihood …

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 …

continuously or with some jumps. This view is widely held in the forecasting literature and under this view, the time series … contemporary forecasting methods is compared to ours using a number of macroeconomic data. …

distribution theory involves cube-root asymptotics and it is used to shed light on forecasting practice. We show that the … conventional forecasting methods do not necessarily produce the best forecasts in our setting. We also propose a new forecasting … strategy, which incorporates our new distribution theory, and apply our forecasting method to numerous macroeconomic data. The …

decomposing, smoothing and forecasting two-dimensional sparse data. In some ways, ROPES is similar to Ridge Regression, the LASSO … practical method of forecasting mortality rates, as well as a new method for interpolating and extrapolating sparse longitudinal …

exponential smoothing for forecasting. There is, however, a puzzle. Should the count of the seed states be incorporated into the …