Estimation of a Covariance Matrix under Stein's Loss
Dey, Dipak K. ; Srinivasan, C.
Ann. Statist., Tome 13 (1985) no. 1, p. 1581-1591 / Harvested from Project Euclid
Text on Project Euclid
PDF
Alt PDF
Stein's general technique for improving upon the best invariant unbiased and minimax estimators of the normal covariance matrix is described. The technique is to obtain solutions to a certain differential inequality involving the eigenvalues of the sample covariance matrix. Several improved estimators are obtained by solving the differential inequality. These estimators shrink or expand the sample eigenvalues depending on their magnitude. A scale invariant, adaptive minimax estimator is also obtained.
Publié le : 1985-12-14
Classification:  Covariance matrix,  Wishart distribution,  Stein's loss,  orthogonally invariant estimators,  minimax estimators,  62F10,  62C99 
@article{1176349756,
     author = {Dey, Dipak K. and Srinivasan, C.},
     title = {Estimation of a Covariance Matrix under Stein's Loss},
     journal = {Ann. Statist.},
     volume = {13},
     number = {1},
     year = {1985},
     pages = { 1581-1591},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176349756}
}

Dey, Dipak K.; Srinivasan, C. Estimation of a Covariance Matrix under Stein's Loss. Ann. Statist., Tome 13 (1985) no. 1, pp.  1581-1591. http://gdmltest.u-ga.fr/item/1176349756/