In this paper a procedure for testing additivity in nonlinear time series analysis is provided. The method is based on: Generalized Likelihood Ratio Test(Zhang, 2001), Volterra expansion (Chen et al., 1995), and nonparametric conditional bootstrap (Jianqing and Qiwei, 2003). Investigations about performance (in terms of empirical size and power), and comparisons with other additivity tests proposed by Chen et al. (1995), are made recurring to Monte Carlo simulations.

Bagnato, L., Punzo, A., Nonparametric bootstrap test for autoregressive additive models, <<STATISTICS IN TRANSITION>>, 2009; 10 (Dicembre): 359-370 [http://hdl.handle.net/10807/41325]

Nonparametric bootstrap test for autoregressive additive models

Bagnato, Luca;
2009

Abstract

In this paper a procedure for testing additivity in nonlinear time series analysis is provided. The method is based on: Generalized Likelihood Ratio Test(Zhang, 2001), Volterra expansion (Chen et al., 1995), and nonparametric conditional bootstrap (Jianqing and Qiwei, 2003). Investigations about performance (in terms of empirical size and power), and comparisons with other additivity tests proposed by Chen et al. (1995), are made recurring to Monte Carlo simulations.
2009
Inglese
Bagnato, L., Punzo, A., Nonparametric bootstrap test for autoregressive additive models, <<STATISTICS IN TRANSITION>>, 2009; 10 (Dicembre): 359-370 [http://hdl.handle.net/10807/41325]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/41325
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