On residual sums of squares in non-parametric autoregression

B. Cheng and Howell Tong

Stochastic Processes and their Applications, 1993, vol. 48, issue 1, 157-174

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.

Keywords: bias; cross; validation; kernel; non-parametric; autoregression; residual; sum; of; squares; U-statistics (search for similar items in EconPapers)
Date: 1993
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