Cita:
Statistics & Probability Letters, (15 Oct. 2003), 65(1), 13-20.
ISSN:
0167-7152
DOI:
10.1016/S0167-7152(03)00214-1
Agradecimientos:
We would like to thank Mike Wiper for his careful reading which greatly improved the paper. This research was partially supported by the CYCIT project BEC 2000-0167 and by the Cátedra de Calidad BBVA.
In this paper we consider a sieve bootstrap method for constructing nonparametric prediction intervals for a general class of linear processes. We show that the sieve bootstrap provides consistent estimators of the conditional distribution of future values givIn this paper we consider a sieve bootstrap method for constructing nonparametric prediction intervals for a general class of linear processes. We show that the sieve bootstrap provides consistent estimators of the conditional distribution of future values given the observed data.[+][-]
