摘要翻译：
针对潜在非平稳多元未观测分量模型，提出了分式积分和协整的简便推理方法。基于状态空间表示的有限阶ARMA近似，极大似然估计可以利用EM算法及相关技术。该方法在计算量和逼近质量方面都优于常用的自回归或移动平均截断法。Monte Carlo仿真结果表明，该方法对不同复杂度和维数的过程具有良好的估计性能。
---
英文标题：
《Approximate State Space Modelling of Unobserved Fractional Components》
---
作者：
Tobias Hartl and Roland Weigand
---
最新提交年份：
2020
---
分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
--

---
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.
---
PDF链接：
https://arxiv.org/pdf/1812.09142