Tests for Seasonal Moving Average Unit Root in ARIMA Models
ARIMA模型中季节移动平均单位根的检验AI 解读 ↓
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ARIMA模型中季节移动平均单位根的检验AI 解读 ↓
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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.