A Minimax Criterion for Choosing Weight Functions for $L$-Estimates of Location
Mason, David M.
Ann. Statist., Tome 11 (1983) no. 1, p. 317-325 / Harvested from Project Euclid
Let $X_1, \cdots, X_n$ be independent with common distribution $F$ symmetric about $\mu$. Let $T_n = n^{-1} \sum^n_{i = 1} J(i/(n + 1))X_{in}$ be an $L$-estimate of $\mu$ based on a weight function $J$ and the order statistics $X_{1n} \leq \cdots \leq X_{nn}$ of $X_1, \cdots, X_n$. Under very general regularity conditions $n^{1/2}T_n$ has asymptotic variance $\sigma^2(J, F)$. A weight function $J_0$ is found that minimizes the maximum of $\sigma^2(J, F)/s^2(F)$, whenever $s(F)$ is a measure of scale of a general type, as $F$ ranges over a subclass of the symmetric distributions determined by $s(F)$ and $J$ ranges over a class of weight functions also determined by $s(F)$. The sample mean and the trimmed mean arise as the solutions for particular choices of scale measures.
Publié le : 1983-03-14
Classification:  $L$-estimates for location,  order statistics,  minimax,  weight function,  62G35,  62G05
@article{1176346082,
     author = {Mason, David M.},
     title = {A Minimax Criterion for Choosing Weight Functions for $L$-Estimates of Location},
     journal = {Ann. Statist.},
     volume = {11},
     number = {1},
     year = {1983},
     pages = { 317-325},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176346082}
}
Mason, David M. A Minimax Criterion for Choosing Weight Functions for $L$-Estimates of Location. Ann. Statist., Tome 11 (1983) no. 1, pp.  317-325. http://gdmltest.u-ga.fr/item/1176346082/