切换VAR及其相关模型的平稳性
Stationarity of Switching VAR and Other Related Models
摘要：
切换ARMA模型极大地增强了标准线性模型的性能，使得不同的区域可以采用不同的ARMA模型，并且区域切换通常假设为潜在区域有限状态上的马尔可夫链。虽然统计问题一直是最近许多论文的主题，但很少有系统的研究这一类新的非线性模型的概率方面。本文通过对SVAR模型的研究，讨论了这类模型的一些基本问题，包括严格平稳性、初始条件的影响、二阶性质等。文中给出了一些例子来说明理论和各种应用。扩展到其他模型，如均值漂移，和非均匀转移概率进行了讨论。
英文摘要：
Switching ARMA models greatly enhance the standard linear models to the extent that different ARMA model is allowed in a different regime, and the regime switching is typically assumed a Markov chain on the finite states of potential regimes. Although statistical issues have been the subject of many recent papers, there is few systematic study of the probabilistic aspects of this new class of nonlinear models. This paper discusses some basic issues concerning this class of models including strict stationarity, influence of initial conditions, and second-order property by studying SVAR models. A number of examples are given to illustrate the theory and the variety of applications. Extensions to other models such as mean-shifting, and inhomogeneous transition probabilities are discussed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
