论文标题
动态广义因子分析模型中的隐藏因子估计
Hidden Factor estimation in Dynamic Generalized Factor Analysis Models
论文作者
论文摘要
本文通过概括了卡尔曼过滤，介绍了动态通用因子分析中隐藏因素的估计。讨论了渐近的一致性，并表明卡尔曼一步预测指标不是正确的工具，而纯滤波器会产生一致的估计值。
This paper deals with the estimation of the hidden factor in Dynamic Generalized Factor Analysis via a generalization of Kalman filtering. Asymptotic consistency is discussed and it is shown that the Kalman one-step predictor is not the right tool while the pure filter yields a consistent estimate.
