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分类依据与纠错

AI 根据所提供的论文材料归类:摘要直接研究 ARIMA 差分阶数、移动平均单位根与给定向量下的协整检验。

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代码、数据与补充材料

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关注这篇论文的作者
Pentti Saikkonen
Ritva Luukkonen

ARIMA 模型差分阶数的点最优检验

研究问题
如何以原序列平稳为原假设、以一阶单整为备择来判断差分阶数,并将这一思路用于检验给定理论向量下的协整?
方法与思路
作者反转常见自回归单位根检验的假设方向,将平稳序列差分产生的过度差分转为移动平均单位根检验问题。
材料陈述的贡献
摘要提出以平稳性为原假设的检验路径,并说明相关程序可用于检验多变量序列是否按给定理论协整向量协整。
阅读关注点
应核对移动平均单位根与原序列平稳性的对应、点最优检验的设计备择,以及协整应用中向量给定与其他参数的处理。
阅读边界
仅据所给 Crossref 摘要,无法判断点最优性的具体标准、临界值或功效;给定协整向量的检验不等同于一般协整秩检验。

原文摘要

Deciding the order of differencing is an important part in the specification of an autoregressive integrated moving average (ARIMA) mode. In most, though not all, cases this means deciding whether to use the original observations or their first differences. Common test procedures used in this context are some variants of autoregressive unit root tests. In these tests, one tests the null hypothesis that the order of differencing is one against the alternative that it is zero. The null hypothesis thus states that the original series is nonstationary and integrated of order one, whereas the alternative assumes that it is stationary. In this paper the situation is reversed so that our null hypothesis states that the original series is stationary, whereas the alternative states that it is integrated of order one. In our approach the use of a differenced series thus means overdifferencing and, consequently, a model with a moving average unit root. Testing for this moving average unit root is the topic of this paper. As discussed by Saikkonen and Luukkonen [26] and Tanaka [31], test procedures obtained for this null hypothesis can also be used to test the null hypothesis that a multivariate time series is cointegrated with a given theoretical cointegrating vector. Since the null hypothesis of cointegration is often of interest and cannot be naturally tested by autoregressive unit root tests, this connection provides an important motivation for the test procedures of this paper.

笔记与分组
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