Abstract
The usual ordering of linear experiments is defined by quadratic risk of attainable linear estimators. It is shown that under normality assumption this ordering can be introduced in a risk-free way by stochastic ordering of the estimators. Moreover an application of Schur-convex functions to design of experiments is presented.
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Partly supported by CPBP 0.1.02.
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Stępniak, C. Stochastic ordering and schur-convex functions in comparison of linear experiments. Metrika 36, 291–298 (1989). https://doi.org/10.1007/BF02614102
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DOI: https://doi.org/10.1007/BF02614102