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On residual sums of squares in non-parametric autoregression

Author

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  • Cheng, B.
  • Tong, H.

Abstract

By relying on the theory of U-statistics of dependent data, we have given a detailed analysis of the residual sum of squares, RSS, after fitting a nonlinear autoregression using the kernel method. The asymptotic bias of the RSS as an estimator of the noise variance is evaluated up to and including the first order term. A similar quantity, the cross validated residual sum of squares obtained by 'leaving one out' in the fitting is similarly analysed. An asymptotic positive bias is obtained.

Suggested Citation

  • Cheng, B. & Tong, H., 1993. "On residual sums of squares in non-parametric autoregression," Stochastic Processes and their Applications, Elsevier, vol. 48(1), pages 157-174, October.
    • Handle: RePEc:eee:spapps:v:48:y:1993:i:1:p:157-174
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