Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Weinstein, Asaf"'
Autor:
Weinstein, Asaf
Simultaneous statistical inference problems are at the basis of almost any scientific discovery process. We consider a class of simultaneous inference problems that are invariant under permutations, meaning that all components of the problem are obli
Externí odkaz:
http://arxiv.org/abs/2110.06250
Variable selection properties of procedures utilizing penalized-likelihood estimates is a central topic in the study of high dimensional linear regression problems. Existing literature emphasizes the quality of ranking of the variables by such proced
Externí odkaz:
http://arxiv.org/abs/2007.15346
Autor:
Weinstein, Asaf
In a compound decision problem, consisting of $n$ statistically independent copies of the same problem to be solved under the sum of the individual losses, any reasonable compound decision rule $\delta$ satisfies a natural symmetry property, entailin
Externí odkaz:
http://arxiv.org/abs/1911.11422
In a given generalized linear model with fixed effects, and under a specified loss function, what is the optimal estimator of the coefficients? We propose as a contender an ideal (oracle) shrinkage estimator, specifically, the Bayes estimator under t
Externí odkaz:
http://arxiv.org/abs/1908.08444
Autor:
Weinstein, Asaf, Ramdas, Aaditya
The false coverage rate (FCR) is the expected ratio of number of constructed confidence intervals (CIs) that fail to cover their respective parameters to the total number of constructed CIs. Procedures for FCR control exist in the offline setting, bu
Externí odkaz:
http://arxiv.org/abs/1905.01059
Knockoffs is a new framework for controlling the false discovery rate (FDR) in multiple hypothesis testing problems involving complex statistical models. While there has been great emphasis on Type-I error control, Type-II errors have been far less s
Externí odkaz:
http://arxiv.org/abs/1712.06465
Autor:
Weinstein, Asaf, Yekutieli, Daniel
Publikováno v:
Statistica Sinica, 2020 Jan 01. 30(1), 531-555.
Externí odkaz:
https://www.jstor.org/stable/26892795
Inference after model selection has been an active research topic in the past few years, with numerous works offering different approaches to addressing the perils of the reuse of data. In particular, major progress has been made recently on large an
Externí odkaz:
http://arxiv.org/abs/1605.08824
We develop an empirical Bayes procedure for estimating the cell means in an unbalanced, two-way additive model with fixed effects. We employ a hierarchical model, which reflects exchangeability of the effects within treatment and within block but not
Externí odkaz:
http://arxiv.org/abs/1605.08466
The problem of estimating the mean of a normal vector with known but unequal variances introduces substantial difficulties that impair the adequacy of traditional empirical Bayes estimators. By taking a different approach, that treats the known varia
Externí odkaz:
http://arxiv.org/abs/1503.08503