منابع مشابه
`p-norm based James-Stein estimation with minimaxity and sparsity
A new class of minimax Stein-type shrinkage estimators of a multivariate normal mean is studied where the shrinkage factor is based on an `p norm. The proposed estimators allow some but not all coordinates to be estimated by 0 thereby allow sparsity as well as minimaxity. AMS 2000 subject classifications: Primary 62C20; secondary 62J07.
متن کاملJames-Stein state filtering algorithms
In 1961, James and Stein discovered a remarkable estimator that dominates the maximum-likelihood estimate of the mean of a p-variate normal distribution, provided the dimension p is greater than two. This paper extends the James–Stein estimator and highlights benefits of applying these extensions to adaptive signal processing problems. The main contribution of this paper is the derivation of th...
متن کاملCluster-Seeking James-Stein Estimators
This paper considers the problem of estimating a high-dimensional vector of parameters θ ∈ R from a noisy observation. The noise vector is i.i.d. Gaussian with known variance. For a squared-error loss function, the James-Stein (JS) estimator is known to dominate the simple maximum-likelihood (ML) estimator when the dimension n exceeds two. The JS-estimator shrinks the observed vector towards th...
متن کاملEmpirical Bayes and the James–Stein Estimator
Charles Stein shocked the statistical world in 1955 with his proof that maximum likelihood estimation methods for Gaussian models, in common use for more than a century, were inadmissible beyond simple oneor twodimensional situations. These methods are still in use, for good reasons, but Stein-type estimators have pointed the way toward a radically different empirical Bayes approach to high-dim...
متن کاملJames-Stein type estimators of variances
In this paper we propose James–Stein type estimators for variances raised to a fixed power by shrinking individual variance estimators towards the arithmetic mean. We derive and estimate the optimal choices of shrinkage parameters under both the squared and the Stein loss functions. Asymptotic properties are investigated under two schemes when either the number of degrees of freedom of each ind...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ETS Research Report Series
سال: 1989
ISSN: 2330-8516
DOI: 10.1002/j.2330-8516.1989.tb00346.x