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pro vyhledávání: '"Greenshtein, Eitan"'
Autor:
Greenshtein, Eitan
{\bf Abstract} Consider a Non-Parametric Empirical Bayes (NPEB) setup. We observe $Y_i, \sim f(y|\theta_i)$, $\theta_i \in \Theta$ independent, where $\theta_i \sim G$ are independent $i=1,...,n$. The mixing distribution $G$ is unknown $G \in \{G\}$
Externí odkaz:
http://arxiv.org/abs/2405.05656
Autor:
Greenshtein, Eitan, Ritov, Ya'acov
Let $f(y|\theta), \; \theta \in \Omega$ be a parametric family, $\eta(\theta)$ a given function, and $G$ an unknown mixing distribution. It is desired to estimate $E_G (\eta(\theta))\equiv \eta_G$ based on independent observations $Y_1,...,Y_n$, wher
Externí odkaz:
http://arxiv.org/abs/2107.09296
Autor:
Greenshtein, Eitan, Ritov, Ya'acov
Consider the problem of estimating a weighted average of the means of $n$ strata, based on a random sample with realized $K_i$ observations from stratum $i, \; i=1,...,n$. This task is non-trivial in cases where for a significant portion of the strat
Externí odkaz:
http://arxiv.org/abs/1909.09336
Autor:
Greenshtein, Eitan, Itskov, Theodor
Let $(Y_i,\theta_i)$, $i=1,...,n$, be independent random vectors distributed like $(Y,\theta) \sim G^*$, where the marginal distribution of $\theta$ is completely unknown, and the conditional distribution of $Y$ conditional on $\theta$ is known. It i
Externí odkaz:
http://arxiv.org/abs/1406.5840
Autor:
Greenshtein, Eitan, Ritov, Ya'acov
Publikováno v:
Statistical Science, 2019 May 01. 34(2), 224-228.
Externí odkaz:
https://www.jstor.org/stable/26771051
Autor:
Greenshtein, Eitan, Itskov, Theodor
We elaborate on a deconvolution method, used to estimate the empirical distribution of unknown parameters, as suggested recently by Efron (2013). It is applied to estimating the empirical distribution of the 'sampling probabilities' of m sampled item
Externí odkaz:
http://arxiv.org/abs/1309.2136
Autor:
Brown, Lawrence D., Greenshtein, Eitan
Publikováno v:
Annals of Statistics 2009, Vol. 37, No. 4, 1685-1704
We consider the classical problem of estimating a vector $\bolds{\mu}=(\mu_1,...,\mu_n)$ based on independent observations $Y_i\sim N(\mu_i,1)$, $i=1,...,n$. Suppose $\mu_i$, $i=1,...,n$ are independent realizations from a completely unknown $G$. We
Externí odkaz:
http://arxiv.org/abs/0908.1712
Autor:
Greenshtein, Eitan, Ritov, Ya'acov
We consider the compound decision problem of estimating a vector of $n$ parameters, known up to a permutation, corresponding to $n$ independent observations, and discuss the difference between two symmetric classes of estimators. The first and larger
Externí odkaz:
http://arxiv.org/abs/0802.1319
Autor:
Greenshtein, Eitan, Itskov, Theodor
Publikováno v:
Statistica Sinica, 2018 Jan 01. 28(4), 2189-2208.
Externí odkaz:
https://www.jstor.org/stable/26511207
Autor:
Greenshtein, Eitan
Publikováno v:
Annals of Statistics 2006, Vol. 34, No. 5, 2367-2386
Let $(Y,X_1,...,X_m)$ be a random vector. It is desired to predict $Y$ based on $(X_1,...,X_m)$. Examples of prediction methods are regression, classification using logistic regression or separating hyperplanes, and so on. We consider the problem of
Externí odkaz:
http://arxiv.org/abs/math/0702684