In this paper a sieve bootstrap scheme, the Neural Network Sieve bootstrap for nonlinear time series is proposed. The approach, which is nonparametric in its spirit, does not have the problems of other nonparametric bootstrap techniques such as the blockwise schemes. The procedure performs similarly to the AR-Sieve bootstrap for lineae process while it outperforms the AR-Sieve bootstrap and the moving block bootstrap for nonlinear processes, both in terms of bias and variability.
Neural Network Sieve Bootstrap for Nonlinear Time Series
LA ROCCA, Michele;PERNA, Cira;GIORDANO, Francesco
2005-01-01
Abstract
In this paper a sieve bootstrap scheme, the Neural Network Sieve bootstrap for nonlinear time series is proposed. The approach, which is nonparametric in its spirit, does not have the problems of other nonparametric bootstrap techniques such as the blockwise schemes. The procedure performs similarly to the AR-Sieve bootstrap for lineae process while it outperforms the AR-Sieve bootstrap and the moving block bootstrap for nonlinear processes, both in terms of bias and variability.File in questo prodotto:
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