Abstract. The idea of fractional differencing is introduced in terms of the infinite filter that corresponds to the expansion of (1‐B)d. When the filter is applied to white noise, a class of time series is generated with distinctive properties, particularly in the very low frequencies and pro...... hiện toàn bộ
Abstract. The definitions of fractional Gaussian noise and integrated (or fractionally differenced) series are generalized, and it is shown that the two concepts are equivalent. A new estimator of the long memory parameter in these models is proposed, based on the simple linear regression of the log periodogram on a deterministic regressor. The estimator is the ordi...... hiện toàn bộ
A new test is proposed for cointegration in a single‐equation framework where the regressors are weakly exogenous for the parameters of interest. The test is denoted as an error‐correction mechanism (ECM) test and is based upon the ordinary least squares coefficient of the lagged dependent variable in an autoregressive distributed lag model augmented with leads of the regressors. The limit...... hiện toàn bộ
Abstract. An approach to smoothing and forecasting for time series with missing observations is proposed. For an underlying state‐space model, the EM algorithm is used in conjunction with the conventional Kalman smoothed estimators to derive a simple recursive procedure for estimating the parameters by maximum likelihood. An example is given which involves smoothing...... hiện toàn bộ
Abstract. Squared‐residual autocorrelations have been found useful in detecting nonlinear types of statistical dependence in the residuals of fitted autoregressive‐moving average (ARMA) models (Granger and Andersen, 1978; Miller, 1979). In this note it is shown that the normalized squared‐residual autocorrelations are asymptotically unit multivariate normal. The res...... hiện toàn bộ
Abstract. Stable autoregressive (AR) and autoregressive moving average (ARMA) processes belong to the class of stationary linear time series. A linear time series { hiện toàn bộ
Abstract. The problem of estimating the threshold parameter, i.e., the change point, of a threshold autoregressive model is studied. By introducing smoothness into the model, sampling properties of the conditional least‐squares estimate may be obtained. Artificial and real data are used for illustrations.
Abstract. Local high‐order polynomial fitting is employed for the estimation of the multivariate regression function m(x1,…xd) =E{φ(Yd)φX... hiện toàn bộ
Abstract. Time series with a changing conditional variance have been found useful in many applications. Residual autocorrelations from traditional autoregressive moving‐average models have been found useful in model diagnostic checking. By analogy, squared residual autocorrelations from fitted conditional heteroskedastic time series models would be useful in checkin...... hiện toàn bộ
Abstract. We compare several estimators for the second‐order autoregressive process and compare the associated tests for a unit root. Monte Carlo results are reported for the ordinary least squares estimator, the simple symmetric least squares estimator and the weighted symmetric least squares estimator. The weighted symmetric least squares estimator of the autoregr...... hiện toàn bộ