In this paper we consider the inferential aspect of the nonparametric estimation of a conditional function g(x; φ) = E[φ(Xt)|Xt,m], where Xt,m represents the vector containing the m conditioning lagged values of the series. Here φ is an arbitrary measurable function. The local polynomial estimator of order p is used for the estimation of the function g, and of its partial derivatives up to a total order p. We consider α-mixing processes, and we propose the use of a particular resampling method, the local polynomial bootstrap, for the approximation of the sampling distribution of the estimator. After analyzing the consistency of the proposed method, we present a simulation study which gives evidence of its finite sample behaviour.

Bootstrap inference in local polynomial regression of time series

PARRELLA, Maria Lucia;VITALE, Cosimo Damiano
2007

Abstract

In this paper we consider the inferential aspect of the nonparametric estimation of a conditional function g(x; φ) = E[φ(Xt)|Xt,m], where Xt,m represents the vector containing the m conditioning lagged values of the series. Here φ is an arbitrary measurable function. The local polynomial estimator of order p is used for the estimation of the function g, and of its partial derivatives up to a total order p. We consider α-mixing processes, and we propose the use of a particular resampling method, the local polynomial bootstrap, for the approximation of the sampling distribution of the estimator. After analyzing the consistency of the proposed method, we present a simulation study which gives evidence of its finite sample behaviour.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/1516228
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact