Minimax Estimation of Location Vectors for a Wide Class of Densities
Berger, James
Ann. Statist., Tome 3 (1975) no. 1, p. 1318-1328 / Harvested from Project Euclid
Assume $X = (X_1,\cdots, X_p)^t$ has a $p$-variate density, with respect to Lebesgue measure, of the form $f((x - \theta)^t\not\sum^{-1}(x - \theta))$. Here $\not\sum$ is a known positive definite $p \times p$ matrix and $p \geqq 3$. Assume either (i) $f$ is completely monotonic, or (ii) there exist $\alpha > 0$ and $K > 0$ for which $h(s) = f(s)e^{\alpha s}$ is nondecreasing and nonzero if $s > K$. Then for estimating $\theta$ under a known quadratic loss, classes of minimax estimators are found.
Publié le : 1975-11-14
Classification:  Minimax estimators,  quadratic loss,  completely monotonic,  location parameter,  62C99,  62F10,  62H99
@article{1176343287,
     author = {Berger, James},
     title = {Minimax Estimation of Location Vectors for a Wide Class of Densities},
     journal = {Ann. Statist.},
     volume = {3},
     number = {1},
     year = {1975},
     pages = { 1318-1328},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176343287}
}
Berger, James. Minimax Estimation of Location Vectors for a Wide Class of Densities. Ann. Statist., Tome 3 (1975) no. 1, pp.  1318-1328. http://gdmltest.u-ga.fr/item/1176343287/