Robust Identification of Autoregressive Moving Average Models
提出了一类稳健估计单变量平稳时间序列偏自相关函数的方法，并可从估计的偏自相关系数得到自相关函数估计，适用于观测数据含少量异常值时初步识别ARMA模型的阶数p和q。
SUMMARY We introduce a class of robust estimates for the partial autocorrelation function of a univariate stationary time series and show that it is possible to produce an estimate of the autocorrelation function from the estimated partial autocorrelation coefficients. These statistics seem suitable for the preliminary identification of the order, p and q of an ARMA (p, q) model when the observed series contains a few aberrant observations.