A General Class of Holt-Winters Type Forecasting Models
提出一类广义的短期预测模型，包含水平、增长和季节性的更新机制，并证明其等价于特定ARIMA模型，认为这类模型比Box-Jenkins模型更适合社会经济应用。
This paper is concerned with the formulation of short-term forecasting models, and introduces a range of models of considerable importance. These are defined in terms of predictions and sensible updating mechanisms for estimates of quantities such as level, growth, and seasonality, and constitute generalizations of familiar (linear) exponential smoothing predictors. They are shown to be equivalent to particular ARIMA models, and generally these do not lie within that subset of the ARIMA class which forms the basis of the Box-Jenkins modelling approach. It is argued that the models of this paper have a reasoned structure, and are to be preferred to the Box-Jenkins models for most socio-economic applications.