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Barankin Vector Locally Best Unbiased Estimates
Published 30 Jun 2017 in stat.ML, cs.IT, math.IT, and math.PR | (1706.10062v1)
Abstract: The Barankin bound is generalized to the vector case in the mean square error sense. Necessary and sufficient conditions are obtained to achieve the lower bound. To obtain the result, a simple finite dimensional real vector valued generalization of the Riesz representation theorem for Hilbert spaces is given. The bound has the form of a linear matrix inequality where the covariances of any unbiased estimator, if these exist, are lower bounded by matrices depending only on the parametrized probability distributions.
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