Least squares estimation in dynamic-disturbance time series models
动态扰动时间序列模型的最小二乘估计
Recent results of the author concerning large-sample properties of the nonlinear least squares estimates of the parameters, in a regression model in which the disturbances follow a stationary mixed autoregressive-moving average time series, are extended to models in which lagged values of the dependent and independent variables occur.