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- W2020341508 abstract "Abstract We prove the asymptotic normality of the trimmed mean, obtained by deleting the data which is further away from a parameter of location θ n . To get this trimmed mean, equivariant by rotations, dilations and translations, we choose θ n in a class of multivariate parameters of location, which are equivariant by these transformations. Given the data X 1 , … , X n , we take as θ n , the value such that n −1 ∑ j=1 n h(|X j −θ n |)= inf n −1 ∑ j=1 n h(|X j −θ|), where h is a nondecreasing function and | x | is the Euclidean distance in B d . This estimator θ n is equivariant by rotations and translations. If h ( x ) = x p , θ n is also equivariant by dilations." @default.
- W2020341508 created "2016-06-24" @default.
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- W2020341508 date "1995-10-01" @default.
- W2020341508 modified "2023-10-04" @default.
- W2020341508 title "Asymptotic normality of multivariate trimmed means" @default.
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- W2020341508 doi "https://doi.org/10.1016/0167-7152(94)00204-l" @default.
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