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Asymptotic equivalence of nonparametric regression and white noise model has its limits

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  • Efromovich, Sam
  • Samarov, Alex

Abstract

One of the common themes of the modern nonparametric functional estimation folklore is that the signal-in-white-noise model can serve as a prototype for nonparametric regression. In this note we give an example showing that it may not always be the case

Suggested Citation

  • Efromovich, Sam & Samarov, Alex, 1996. "Asymptotic equivalence of nonparametric regression and white noise model has its limits," Statistics & Probability Letters, Elsevier, vol. 28(2), pages 143-145, June.
    • Handle: RePEc:eee:stapro:v:28:y:1996:i:2:p:143-145
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    Citations

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    Cited by:

    1. Nagel, Eva-Renate & Dette, Holger & Neumeyer, Natalie, 2004. "Bootstrap tests for the error distribution in linear and nonparametric regression models," Technical Reports 2004,38, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    2. Mathias Trabs, 2011. "Calibration of selfdecomposable Lévy models," SFB 649 Discussion Papers SFB649DP2011-073, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Denis Belomestny & Markus Reiß, 2006. "Spectral calibration of exponential Lévy models," Finance and Stochastics, Springer, vol. 10(4), pages 449-474, December.
    4. Mariucci, Ester, 2016. "Asymptotic equivalence for pure jump Lévy processes with unknown Lévy density and Gaussian white noise," Stochastic Processes and their Applications, Elsevier, vol. 126(2), pages 503-541.
    5. Efromovich, Sam, 2003. "On the limit in the equivalence between heteroscedastic regression and filtering model," Statistics & Probability Letters, Elsevier, vol. 63(3), pages 239-242, July.

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