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Adaptive ridge estimator in a linear regression model with spherically symmetric error under constraint

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  • Younes Ommane
  • Idir Ouassou

Abstract

We consider adaptive ridge regression estimators in the general linear model with homogeneous spherically symmetric errors. A restriction on the parameter of regression is considered. We assume that all components are non negative (i.e. on the positive orthant). For this setting, we produce under general quadratic loss such estimators whose risk function dominates that of the least squares provided the number of regressors in the least fore.

Suggested Citation

  • Younes Ommane & Idir Ouassou, 2020. "Adaptive ridge estimator in a linear regression model with spherically symmetric error under constraint," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(1), pages 1-15, January.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:1:p:1-15
    DOI: 10.1080/03610926.2018.1532006
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