On the Bayesian Steady Forecasting Model
本文检验了Smith提出的广义稳态预测模型，发现当观测变量服从指数族分布时，该模型不一定能得到满足传统稳态预测约束的预测值，并用两个特例说明。
Summary A recent criterion of Smith (1979) seeks to generalize the steady forecasting model of Harrison and Stevens (1976) to take account of non-normality in the observation and system variables. In this note, predictive distributions and forecasts corresponding to quadratic and step loss functions are examined when the observation variable has a distribution belonging to the exponential family. It is shown that Smith's generalized model does not always yield forecasts which satisfy constraints obtained from the more familiar forms of steady forecasting. Two particular cases of the exponential family are used to illustrate the point.