Bootstrap inference in local polynomial regression of time series |
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Authors: | Maria Lucia Parrella Cosimo Vitale |
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Affiliation: | (1) Dipartimento di Scienze Economiche e Statistiche, Università di Salerno, Fisciano (SA), Italy |
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Abstract: | In this paper we consider the inferential aspect of the nonparametric estimation of a conditional function , where X t,m represents the vector containing the m conditioning lagged values of the series. Here 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. |
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Keywords: | Nonparametric regression Local polynomial fitting Local bootstrap α -mixing processes |
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