In statistics, an invariant estimator is a criterion that can be used to compare the properties of different estimators, formalising the idea that an estimator should have certain intuitively appealing qualities. Strictly speaking, "invariant" would mean that the estimates themselves are unchanged when both the measurements and the parameters are transformed in a compatible way, but the meaning has been extended to allow the estimates to change in appropriate ways with such transformations.
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- In statistics, an invariant estimator is a criterion that can be used to compare the properties of different estimators, formalising the idea that an estimator should have certain intuitively appealing qualities. Strictly speaking, "invariant" would mean that the estimates themselves are unchanged when both the measurements and the parameters are transformed in a compatible way, but the meaning has been extended to allow the estimates to change in appropriate ways with such transformations. In formal mathematics, the related term equivariant estimator is used as a precise description of the relation of how the estimator changes in response to changes to the dataset and parameterisation.
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- In statistics, an invariant estimator is a criterion that can be used to compare the properties of different estimators, formalising the idea that an estimator should have certain intuitively appealing qualities. Strictly speaking, "invariant" would mean that the estimates themselves are unchanged when both the measurements and the parameters are transformed in a compatible way, but the meaning has been extended to allow the estimates to change in appropriate ways with such transformations.
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