Best Linear Recursive Estimation for Mixed Linear Models
将固定和完全随机模型的递归估计技术扩展到混合线性模型，利用卡尔曼滤波获得两部分随机模型的递归估计量，并通过极限推导出混合模型的递归公式。
Abstract Recursive estimation techniques for fixed and completely random models are extended to mixed linear models. The Kalman filter is used to obtain recursive estimators for a two-part random model where the second random factor obeys a generalized autoregressive process. By passing to the limit in an appropriate way, recursions for the mixed model are derived.