Nonparametric time series prediction: A semi-functional partial linear modeling

Journal of Multivariate Analysis

Volumn 99, Issue 5, 2008, Pages 834-857

  Aneiros Pérez, Germán ^a   Vieu, Philippe ^b  

^a UNIVERSITY OF A CORUÑA   (Spain)

^b UNIVERSITÉ DE TOULOUSE   (France)

Author keywords

Dependent data; Functional data; Partial linear regression; Semiparametric functional model; Time series prediction

Indexed keywords

EID: 40849085713     PISSN: 0047259X     EISSN: 10957243     Source Type: Journal    
DOI: 10.1016/j.jmva.2007.04.010     Document Type: Article

References (15)

1. Aneiros-Pérez G., González-Manteiga W., and Vieu P. Estimation and testing in a partial regression model under long-memory dependence. Bernoulli 10 (2004) 49-78
2. Aneiros-Pérez G., and Vieu P. Semi-functional partial linear regression. Statist. Probab. Lett. 76 (2006) 1102-1110
3. Avramidis P. Two-step cross-validation selection method for partially linear models. Statist. Sinica 15 (2005) 1033-1048
4. D. Bosq, Nonparametric Statistics for Stochastic Processes: Estimation and Prediction, second ed., Lecture Notes in Statistics, vol. 110, Springer, Berlin, 1998.
5. D. Bosq, Linear Processes in Function Spaces. Estimation and Prediction, Lecture Notes in Statistics, vol. 149, Springer, Berlin, 2000.
6. Engle R., Granger C., Rice J., and Weiss A. Nonparametric estimates of the relation between weather and electricity sales. J. Amer. Statist. Assoc. 81 (1986) 310-320
7. Fan J., and Yao Q. Nonlinear Time Series. Nonparametric and Parametric Methods, Springer Series in Statistics (2003), Springer, New York
8. Ferraty F., Goia A., and Vieu P. Functional nonparametric model for time series: a fractal approach to dimension reduction. Test 11 (2002) 317-344
9. F. Ferraty, A. Mas, P. Vieu, Nonparametric regression on functional data: inference and practical aspects, Aust. N.Z. J. Statist. (2007), 10.1111/j.1467-842X.2006.00467.x.
10. Ferraty F., and Vieu P. Nonparametric models for functional data, with applications in regression, curves discrimination and time series prediction. J. Nonparametric Statist. 16 (2004) 111-127
11. Ferraty F., and Vieu P. Nonparametric Functional Data Analysis, Springer Series in Statistics (2006), Springer, New York
12. Ibragimov I.A. Some limit theorems for stationary processes. Theoret. Probab. Appl. 7 (1962) 282-349
13. Masry E. Nonparametric regression estimation for dependent functional data: asymptotic normality. Stochastic Process. Appl. 115 (2005) 155-177
14. Oodaira H., and Yoshihara K.I. The law of the iterated logarithm for stationary processes satisfying mixing conditions. Kodai Math. Sem. Rep. 23 (1971) 311-334
15. Speckman P. Kernel smoothing in partial linear models. J. Roy. Statist. Soc. Ser. B 50 (1988) 413-436