A note on multi-step forecasting with functional coefficient autoregressive models

International Journal of Forecasting

Volumn 21, Issue 4, 2005, Pages 717-727

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

^a MISSISSIPPI STATE UNIVERSITY   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Bootstrap prediction; Multi step prediction; Smoothing; Vector nonlinear time series

Indexed keywords

EID: 25144477678     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2005.04.012     Document Type: Article

References (17)

1. Z. Cai J. Fan & Q. Yao Functional coefficient regression models for nonlinear time series Journal of the American Statistical Association 95 2000 941-956
2. R. Chen A nonparametric multi-step prediction estimator in Markovian structures Statistica Sinica 63 1996 603-615
3. R. Chen & L. Lui Functional coefficient autoregressive models Journal of the American Statistical Association 421 1993 298-308
4. R. Chen & L. Liu Functional coefficient autoregressive models: estimation and tests of hypotheses Journal of Time Series Analysis 222 2001 151-173
5. R. Chen L. Yang & C. Hafner Nonparametric multi-step ahead prediction in time series analysis Journal of the Royal Statistical Society. Series B 66 2004 669-686
6. M. Clements & J. Smith The performance of alternative forecasting methods for SETAR models International Journal of Forecasting 13 1993 463-475
7. M. Clements & J. Smith Evaluating the forecast densities of linear and non-linear models: Application to output growth and unemployment Journal of Forecasting 19 2000 255-276
8. J. DeGooijer & B. Ray Using POLYMARS to model vector time series Computational Statistics & Data Analysis 42 2003 73-90
9. J. Fan & Q. Yao Nonlinear time series: Nonparametric and parametric methods 2003 Springer New York
10. J.L. Harvill & B.K. Ray A note on tests for nonlinearity in a vector time series Biometrika 863 1999 728-734
11. Harvill, J.L., & Ray, B.K. (submitted for publication). Functional coefficient autoregressive models for vector time series. Computational Statistics and Data Analysis.
12. Huang, J.Z. & Shen, H. (2004). Functional coefficient regression models for nonlinear time series: A polynomial spline approach. Technical report, Department of Statistics, University of North Carolina, Chapel Hill.
13. A.L. Montgomery V. Zarnowitz R.S. Tsay & G.C. Tiao Forecasting the U.S. unemployment rate Journal of the American Statistical Association 442 1998 478-493
14. J.M. Pemberton Exact least squares multi-step prediction from nonlinear autoregressive models Journal of Time Series Analysis 8 1987 443-448
15. S.M. Potter A nonlinear approach to US GNP Journal of Applied Econometrics 102 1995 109-125
16. G.C. Tiao & R.S. Tsay Some advances in non-linear and adaptive modeling in time series Journal of Forecasting 13 1994 109-131
17. Van Dijk, D. (1999). Smooth transition models: Extensions and outlier robust inference. PhD Thesis, Erasmus University.