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Equivariant estimator

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A statistical point estimator that preserves the structure of the problem of statistical estimation relative to a given group of one-to-one transformations of a sampling space.

Suppose that in the realization of a random vector , the components of which are independent, identically distributed random variables taking values in a sampling space , , it is necessary to estimate the unknown true value of the parameter . Next, suppose that on acts a group of one-to-one transformations such that

In turn, the group generates on the parameter space a so-called induced group of transformations , the elements of which are defined by the formula

Let be a group of one-to-one transformations on such that

Under these conditions it is said that a point estimator of is an equivariant estimator, or that it preserves the structure of the problem of statistical estimation of the parameter with respect to the group , if

The most interesting results in the theory of equivariant estimators have been obtained under the assumption that the loss function is invariant with respect to .

References

[1] S. Zachs, "The theory of statistical inference" , Wiley (1971)
[2] E.L. Lehmann, "Testing statistical hypotheses" , Wiley (1986)
How to Cite This Entry:
Equivariant estimator. M.S. Nikulin (originator), Encyclopedia of Mathematics. URL: http://www.encyclopediaofmath.org/index.php?title=Equivariant_estimator&oldid=15622
This text originally appeared in Encyclopedia of Mathematics - ISBN 1402006098