Abstract

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.

中文翻译：

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未观察到的分数分量的近似状态空间建模

摘要

我们为具有分数积分和协积分的潜在非平稳多元未观测分量模型提出了方便的推理方法。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。在计算成本和逼近质量方面，逼近优于常用的自回归或移动平均截断。蒙特卡罗模拟揭示了所提出的方法对于不同复杂度和维度的过程的良好估计特性。