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Subsampling, symmetrization, and robust interpolation

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  • Politis, Dimitris N.
  • Romano, Joseph P.
  • Wolf, Michael

Abstract

The recently developed subsampling methodology has been shown to be valid for the construction of large-sample confidence regions for a general unknown parameter e under very minimal conditions. Nevertheless, in some specific cases -e.g. in the case of the sample mean of Li.d. data- it has been noted that the subsampling distribution estimators underperform as compared to alternative estimators such as the bootstrap or the asymptotic normal distribution (with estimated variance). In the present report we investigate the extent to which the performance of subsampling distribution estimators can be improved by a (partial) symmetrization technique, while at the same time retaining the robustness property of consistent distribution estimation even in nonregular cases; both i.i.d. and weakly dependent (mixing) observations are considered.

Suggested Citation

  • Politis, Dimitris N. & Romano, Joseph P. & Wolf, Michael, 1999. "Subsampling, symmetrization, and robust interpolation," DES - Working Papers. Statistics and Econometrics. WS 6343, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:6343
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    1. Babu, G. Jogesh & Singh, Kesar, 1985. "Edgeworth expansions for sampling without replacement from finite populations," Journal of Multivariate Analysis, Elsevier, vol. 17(3), pages 261-278, December.
    2. Romano, Joseph P. & Wolf, Michael, 1998. "Subsampling confidence intervals for the autoregressive root," DES - Working Papers. Statistics and Econometrics. WS 6268, Universidad Carlos III de Madrid. Departamento de Estadística.
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    Cited by:

    1. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, New Economic School (NES).

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    Keywords

    Extrapolation;

    Statistics

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