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Srivastava, M. S.

Comparison of the inverse and classical estimators in multi-univariate linear calibration. (English) Zbl 0875.62217

Commun. Stat., Theory Methods 24, No. 11, 2753-2767 (1995).
Summary: The problem of estimation in the controlled linear calibration with a multivariate response and univariate explanatory variable is considered when the covariance matrix is unknown. It is shown that the classical estimator is inadmissible whereas the inverse estimator is admissible. Both estimators have been shown to be biased (underestimating).

Cited in 1 Review
Cited in 4 Documents

MSC:

62H12 Estimation in multivariate analysis
62C15 Admissibility in statistical decision theory
62F15 Bayesian inference

Keywords:

admissibility; Bayes risk; biased estimators; inverse regression; multivariate normal; shrinkage estimator
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Full Text: DOI

References:

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