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AI 根据所提供的论文材料归类:摘要直接研究季节ARIMA与ARMA模型的移动平均单位根及其检验分布,对应时间序列方法。

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关注这篇论文的作者
Wing-Kuen Tam
Gregory C. Reinsel

ARIMA模型中季节移动平均单位根的检验

研究问题
如何检验季节移动平均算子是否存在单位根,从而区分确定性与随机性季节模式,并推广至更一般的季节模型?
方法与思路
作者研究局部最优不变无偏检验与点最优不变检验,推导有限样本及渐近分布,并按噪声的ARMA结构调整程序。
材料陈述的贡献
摘要称提供季度与月度数据的零假设分位数、有限功效研究及一般模型扩展,并通过模拟和实例考察调整后的程序。
阅读关注点
应核对单位根假设与季节模式解释的关系、局部备择的设定,以及估计噪声ARMA结构对检验有效性的影响。
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仅据版本未注明的 OpenAlex 索引摘要;具体分布条件、临界值及功效数值未提供,推广程序的适用范围需读全文核实。

原文摘要

Procedures to test for a unit root in the seasonal moving average (MA) operator for seasonal autoregressive integrated moving average (ARIMA) models are examined. Such procedures are useful to distinguish deterministic from stochastic seasonal patterns. The simple (integrated) seasonal MA(1) model Z t ≡ Y t - Yt-s = (1 - θB s)ϵt, where {Y t} is the observed seasonal series and {ϵt} is a white noise sequence, is considered, and tests for H 0: θ = 1 versus H 1: θ < 1 are studied. The locally best invariant unbiased and point-optimal invariant tests are investigated. The finite-sample and asymptotic distributions of the test statistics under both the null hypothesis and local alternatives are derived. Quantiles of the null distributions are tabulated for quarterly and monthly data cases, and a limited study of the powers of the tests is reported. The test procedures are extended to more general seasonal ARMA models of the form Z t = (1 - θB s)Nt, where N t follows a general stationary and invertible ARMA model φ(B)Nt = θ*(B)ϵt. The generalizations suggested involve modifying the test procedures for the seasonal MA(1) case parametrically, based on the estimated ARMA structure for the noise process {N t}. Simulation results are presented to study the performance of the modified procedure, and numerical examples involving monthly and quarterly seasonal time series data are given.

笔记与分组
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