Fixed Interval Estimation in State Space Models when Some of the Data are Missing or Aggregated
将卡尔曼滤波固定区间平滑算法扩展到部分观测缺失或聚合且状态协方差矩阵可能奇异的情形，同时估计缺失观测值，并应用于多元自回归移动平均模型的缺失数据插补。
Ansley & Kohn's (1982) geomertical derivation of the Kalman filter fixed-interval smoothing algorthm is extended to the case where some of the observations are missing or aggregated and the state covariance matrix may be singular. Estimates of missing observations are also obtained. The theory is then applied to the interpolation of missing data in mulativariate autoregressive-moving average modles.