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Minimum Riemannian risk equivariant estimator for the univariate normal model

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  • García, Gloria
  • M. Oller, Josep

Abstract

In this paper, we prove the existence and unicity of the minimum risk equivariant estimator for the univariate normal model, under the affine group action, using the square of the Rao distance as the loss function.

Suggested Citation

  • García, Gloria & M. Oller, Josep, 2001. "Minimum Riemannian risk equivariant estimator for the univariate normal model," Statistics & Probability Letters, Elsevier, vol. 52(1), pages 109-113, March.
    • Handle: RePEc:eee:stapro:v:52:y:2001:i:1:p:109-113
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    References listed on IDEAS

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    1. Burbea J. & Oller J. M., 1988. "The Information Metric For Univariate Linear Elliptic Models," Statistics & Risk Modeling, De Gruyter, vol. 6(3), pages 209-222, March.
    2. Burbea, Jacob & Rao, C. Radhakrishna, 1982. "Entropy differential metric, distance and divergence measures in probability spaces: A unified approach," Journal of Multivariate Analysis, Elsevier, vol. 12(4), pages 575-596, December.
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    Cited by:

    1. M. Shams, 2021. "On weakly equivariant estimators," Statistical Papers, Springer, vol. 62(4), pages 1611-1650, August.

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