Increment-vector methodology: Transforming non-stationary series to stationary series

Journal of Applied Probability

Volumn 35, Issue 1, 1998, Pages 64-77

  Chen, Zhao Guo ^a   Anderson, Oliver D ^b  

^a STATISTICS CANADA   (Canada)

^b NONE

Author keywords

ARIMA model; Degree of differencing; Difference equations; Generalized covariance function; Generalized differencing operator; Integrated stationary time series; Intrinsic random function; Polyvariogram; Variogram

Indexed keywords

EID: 0032394606     PISSN: 00219002     EISSN: None     Source Type: Journal    
DOI: 10.1017/S0021900200014686     Document Type: Article

References (9)

1. BOX, G.E.P. AND JENKINS, G.M. (1976). Time Scries. Forecasting and Control. Revised edition. Holden-Day, San Francisco.
2. CHEN, Z.-G. AND ANDERSON, O.D. (1994a). The representation and decomposition of integrated stationary time series. Adv. Appl. Prob. 26, 799-819.
3. CHEN, Z.-G. AND ANDERSON, O.D. (1994b). Polyvariograms and their asymptotes. Submitted for publication.
4. CHEN, Z.-G. AND LIU, J.(1998). A note on forecasting and interpolating seasonal integrated time series. Submitted for publication.
5. CRESSIE, N. (1988). A graphical procedure for determining nonstationarity in time series. J. Amer. Statist. Assoc: 83, 1108-1116. Correction 85, 272 (1990).
6. HILDEBRAND, F.B. (1968). Finite-Difference Equations and Solutions. Prentice Hall, Englewood Cliffs, NJ.
7. LAKSHMIKANTHAM, V. AND TRIGIANTE, D. (1988). Theory of Difference Equations: Numerical Methods and Applications. Academic Press, Boston.
8. MATHERON, G. (1973). The intrinsic random functions and their applications. Adv. Appl. Prob. 5, 439-468.
9. NELSON, C.R. AND PLOSSER, C.I. (1982). Trends and random walks in macroeconomic time series. J. Monetary Econ. 10, 139-162.