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The smoothing dichotomy in nonparametric regression under long‐memory errors

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  • Sándor Csörgő

Abstract

The phenomenon of smoothing dichotomy in random‐design nonparametric regression is exposed in nontechnical terms from two recent papers published jointly with Jan Mielniczuk. This concerns the asymptotic distribution of kernel estimators when the errors exhibit long‐range dependence, being instantaneous functions either of Gaussian sequences or of infinite‐order moving averages, depending on the amount of smoothing.

Suggested Citation

  • Sándor Csörgő, 2002. "The smoothing dichotomy in nonparametric regression under long‐memory errors," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(2), pages 132-142, May.
    • Handle: RePEc:bla:stanee:v:56:y:2002:i:2:p:132-142
    DOI: 10.1111/1467-9574.00188
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    References listed on IDEAS

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    1. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606, November.
    2. Barnett,William A. & Powell,James & Tauchen,George E. (ed.), 1991. "Nonparametric and Semiparametric Methods in Econometrics and Statistics," Cambridge Books, Cambridge University Press, number 9780521424318, November.
    3. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590, November.
    4. Barnett,William A. & Powell,James & Tauchen,George E. (ed.), 1991. "Nonparametric and Semiparametric Methods in Econometrics and Statistics," Cambridge Books, Cambridge University Press, number 9780521370905, November.
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