Robust Sequential Approximate Bayesian Estimation
针对非正态观测数据，提出一种线性时间序列模型位置参数序贯更新的近似方法，检验了所得非线性递归滤波算法的性质，发现其对多种非正态误差分布具有稳健性。
SUMMARY An approximation to the sequential updating of the distribution of location parameters of a linear time series model is developed for non-normal observations. The behaviour of the resulting non-linear recursive filtering algorithm is examined and shown to have certain desirable properties for a variety of non-normal error distributions. Illustrative examples are given and relationships with previous work on robustness and sequential estimation are mentioned.