论文信息 - An efficient method to compute consistent estimates of the AR parameters of an ARMA model

An efficient method to compute consistent estimates of the AR parameters of an ARMA model

A computationally efficient method for consistent estimation of the AR parameters of an ARMA model is obtained, based on an iterated least squares approach proposed by Tsay and Tiao. The method is derived from the lattice filter structure which generates an orthogonal basis for the Hilbert space of interest. It is shown that for the ARMA(p, q) model, we can get consistent estimates of the AR parameters by using an least squares lattice estimation algorithm and solving a system of q linear equations.

Shiping Li | Bradely Dickinson

[1] Will Gersch,et al. Estimation of the autoregressive parameters of a mixed autoregressive moving-average time series , 1970 .

[2] J. P. Burg,et al. Maximum entropy spectral analysis. , 1967 .

[3] A. Gray,et al. Digital lattice and ladder filter synthesis , 1973 .

[4] M. Morf,et al. Recursive least squares ladder estimation algorithms , 1981 .

[5] George E. P. Box,et al. Time Series Analysis: Forecasting and Control , 1977 .

[6] Lloyd J. Griffiths,et al. Further results of a least squares and gradient adaptive lattice algorithm comparison , 1982, ICASSP.

[7] M. Shensa,et al. Recursive least squares lattice algorithms--A geometrical approach , 1981 .

[8] Gwilym M. Jenkins,et al. Time series analysis, forecasting and control , 1972 .

[9] G. C. Tiao,et al. Consistent Estimates of Autoregressive Parameters and Extended Sample Autocorrelation Function for Stationary and Nonstationary ARMA Models , 1984 .

[10] J. Makhoul. A class of all-zero lattice digital filters: Properties and applications , 1978 .

[11] T. Söderström,et al. Instrumental variable methods for system identification , 1983 .