Robust Regression by Means of S-Estimators View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1984

AUTHORS

P. Rousseeuw , V. Yohai

ABSTRACT

There are at least two reasons why robust regression techniques are useful tools in robust time series analysis. First of all, one often wants to estimate autoregressive parameters in a robust way, and secondly, one sometimes has to fit a linear or nonlinear trend to a time series. In this paper we shall develop a class of methods for robust regression, and briefly comment on their use in time series. These new estimators are introduced because of their invulnerability to large fractions of contaminated data. We propose to call them “S-estimators” because they are based on estimators of scale. More... »

PAGES

256-272

References to SciGraph publications

  • 1981-03. Asymptotic behavior of general M-estimates for regression and scale with random carriers in PROBABILITY THEORY AND RELATED FIELDS
  • 1979. Bias- and efficiency-robustness of general M-estimators for regression with random carriers in SMOOTHING TECHNIQUES FOR CURVE ESTIMATION
  • 1985-12. Change-of-variance sensitivities in regression analysis in PROBABILITY THEORY AND RELATED FIELDS
  • 1982-10. Close binary systems before and after mass transfer in ASTROPHYSICS AND SPACE SCIENCE
  • Book

    TITLE

    Robust and Nonlinear Time Series Analysis

    ISBN

    978-0-387-96102-6
    978-1-4615-7821-5

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-1-4615-7821-5_15

    DOI

    http://dx.doi.org/10.1007/978-1-4615-7821-5_15

    DIMENSIONS

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