An investigation of lag identification tools for vector nonlinear time series

Communications in Statistics - Theory and Methods

Volumn 29, Issue 8, 2000, Pages 1677-1701

  Harvill, Jane L ^a   Ray, Bonnie K ^a  

^a NONE

Author keywords

Kendall's ; Mutual information criterion

Indexed keywords

EID: 26844492257     PISSN: 03610926     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (25)

1. Abarbanel, H. and Lall, U. (1996). "Nonlinear Dynamics of the Great Salt Lake: System Identification and Prediction," Climate Dynamics, 12, 287-297.
2. Auestad, B. and Tjostheim, D. (1994). "Nonparametric Identification of Non-linear Time Series: Selecting Significant Lags," J. Am. Statist. Assoc., 89, 1410-1419.
3. Chen R. and Tsay, R.S. (1993). "Nonlinear Additive ARX Models," J. Am. Statist. Assoc., 88, 955-967.
4. Cheng, B. and Tong, H. (1992). "On Consistent Nonparametric Order Determination and Chaos," J. R. Statist. Soc., B, 54, 427-449.
5. Cole, J. and Cook, E. (1998). "The Changing Relationship Between ENSO Variability and Moisture Balance in the Continental United States," Geophysical Research Letters, 25, 4529-4532.
6. Engle, R. (1982). "Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation," Econometrica, 50, 987-1008.
7. Friedman, J. (1991). "Multivariate Adaptive Regression Splines (with Discussion)," Ann. of Statist., 19, 1-142.
8. Friedman, J. and Stuetzle, W. (1981). "Projection Pursuit Regression," J. Amer. Statist. Assoc., 76, 817-823.
9. Fritts, H., Blasing, T., Hayden, B. and Kutzbach, J. (1971). "Multivariate Techniques for Specifying Tree Growth and Climatic Relationships and for Reconstructing Anomalies in Paleoclimate," J. of Appl. Meteorology, 10, 845-864.
10. Granger, C.W.J. (1983). "Forecasting White Noise," Appl. Time Ser. Anal. of Economic Data, (Zellner, A., Ed.). U.S. Dept. of Commerce, Washington, D.C.
11. Granger, C.W.J. and Lin, J. (1994). "Using the Mutual Information Coefficient to Identify Lags in Nonlinear Models," J. Time Ser. Anal., 15, 371-384.
12. Granger, C.W.J. and Teräsvirta, T. (1993). Modeling Nonlinear Economic Relationships, New York: Oxford University Press.
13. Hall, P. and Morton, S.C. (1993). "On the Estimation of Entropy," Ann. Inst. Statist. Math., 45, 69-88.
14. Härdle, W., Tsybakov, A., and Yang, L. (1998). "Nonparametric Vector Autoregression," J. Statist. Plann. Inference, 68, 221-245.
15. Harvill, J.H. and Ray, B.K. (1999). "A Note on Tests for Nonlinearity in a Vector Time Series," Biometrika,
16. Hipel, K.W. and McLeod, A.I. (1994). Time Series Modeling of Water Resources and Environmental Systems, Amsterdam: Elsevier.
17. Joe. H. (1989). "Estimation of Entropy and Other Functionals of a Multivariate Density," Ann. Inst. Statist. Math., 41, 683-697.
18. Kendall, M. (1938). "A New Measure of Rank Correlation," Biometrika, 30, 81-89.
19. Quade, D. (1976). "Nonparametric Partial Correlation," Measurement in the Social Sciences. Edited by H.M. Blalock, Jr., Aldine Publishing Company: Chicago, 369-398.
20. Rao, S. and Wong, W. (1998). "Some Contributions to the Multivariate Nonlinear Time Series and to the Bilinear Models," Dept. of Statistics, University of Manchester Institute of Science and Technology (preprint).
21. Reinsel, G.C. (1993). Elements of Multivariate Time Series Analysis, New York: Springer Verlag.
22. Scott, D. (1992). Multivariate Density Estimation: Theory, Practice, and Visualization, New York: Wiley.
23. Tong, H., Thanoon, B., and Gudmundsson, G. (1985). "Threshold Time Series Modeling of Two Icelandic Riverflow Systems," Water Resources Bulletin, 21, 651-660.
24. Tsay, R.S. (1998). "Testing and Modeling Multivariate Threshold Models," J. Am. Statist. Assoc., 93, 1188-1202.
25. Yao, Q. and Tong, H. (1994). "On Subset Selection in Non-parametric Stochastic Regression," Statist. Sinica, 4, 51-70.