Adjustment of Provisional Mortality Series: The Dynamic Linear Model With Structured Measurement Errors
研究如何用双变量结构模型调整临时死亡率序列，该模型包含共同趋势、季节成分及相关测量误差，并用临时数据预测缺血性心脏病死亡率。
Abstract We consider the problem of adjusting provisional time series using a bivariate structural model with correlated measurement errors. Maximum likelihood estimators and a minimum mean squared error adjustment procedure are derived for a provisional and final series containing common trend and seasonal components. The model also includes measurement errors common to both series and errors that are specific to the provisional series. We illustrate the technique by using provisional data to forecast ischemic heart disease mortality.