A Cross-Validation Filter for Time Series Models
提出一种针对任意状态空间模型计算交叉验证误差及相关统计量的滤波器，比现有方法更高效，并易于处理扩散初始条件，探讨了与固定区间平滑算法的关系。
A filter is presented which computes cross-validation errors and associated statistics for an arbitrary state space model. The procedure is more efficient than an existing approach. Diffuse initial conditions are easily handled using a minor extension. The relationship to the fixed interval smoothing algorithm is investigated.