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Large Sample Properties of Parameter Estimates for Periodic ARMA Models
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2001
Year
Large Sample PropertiesParameter IdentificationParameter EstimatesEngineeringParameter EstimationMixed ParmaEstimation StatisticFinancial Time Series AnalysisBusinessEconometricsSampling TheoryStatistical InferenceParma Parameter EstimatesEstimation TheoryVector AutoregressionStatisticsTime Series EconometricsNonlinear Time Series
This paper studies the asymptotic properties of parameter estimates for causal and invertible periodic autoregressive moving‐average (PARMA) time series models. A general limit result for PARMA parameter estimates with a moving‐average component is derived. The paper presents examples that explicitly identify the limiting covariance matrix for parameter estimates from a general periodic autoregression (PAR), a first‐order periodic moving average (PMA(1)), and the mixed PARMA(1,1) model. Some comparisons and contrasts to univariate and vector autoregressive moving‐average sequences are made.