非观测分数阶分量的近似状态空间建模
Approximate State Space Modelling of Unobserved Fractional Components
摘要：
我们提出了方便的推理方法，潜在的非平稳多元不可观测成分模型的分数积分和协整。基于状态空间表示中的有限阶ARMA近似，最大似然估计可以利用EM算法和相关技术。近似优于常用的自回归或移动平均截断，无论是在计算成本和近似质量方面。蒙特卡罗模拟表明，所提出的方法对不同复杂度和维数的过程具有良好的估计性能。
英文摘要：
We propose convenient inferential methods for potentially nonstationary multivariate unobserved components models with fractional integration and cointegration. Based on finite-order ARMA approximations in the state space representation, maximum likelihood estimation can make use of the EM algorithm and related techniques. The approximation outperforms the frequently used autoregressive or moving average truncation, both in terms of computational costs and with respect to approximation quality. Monte Carlo simulations reveal good estimation properties of the proposed methods for processes of different complexity and dimension.
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