Assessing white noise assumption with semi-parametric additive partial linear models

Tianyong Zhang, Demei Yuan, Jiali Ma and Xuemei Hu ()
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Tianyong Zhang: Chongqing Technology and Business University
Demei Yuan: Chongqing Technology and Business University
Jiali Ma: Chongqing Technology and Business University
Xuemei Hu: Chongqing Technology and Business University

Statistical Papers, 2017, vol. 58, issue 2, No 7, 417-431

Abstract: Abstract In this paper, we present two test statistics for assessing white noise assumption with semi-parametric additive partial linear models. The test statistics are shown to have asymptotic normal or chi-squared distributions under the null hypothesis that the model errors belong to white noise series. By applying R, Monte Carlo experiments are conducted to examine the finite sample performance of the test statistics. Simulation results indicate that the test statistics perform satisfactorily in both estimated sizes and powers.

Keywords: White noise; Semi-parametric additive partial linear models; Empirical likelihood; 62M10; 62H12 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00362-015-0705-z

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