Dynamic adaptive procedures that control the false discovery rate
نویسندگان
چکیده
منابع مشابه
Adaptive Linear Step-up Procedures that control the False Discovery Rate
The linear step-up multiple testing procedure controls the False Discovery Rate (FDR) at the desired level q for independent and positively dependent test statistics. When all null hypotheses are true, and the test statistics are independent and continuous, the bound is sharp. When some of the null hypotheses are not true, the procedure is conservative by a factor which is the proportion m0/m o...
متن کاملProcedures controlling generalized false discovery rate
Procedures controlling error rates measuring at least k false rejections, instead of at least one, can potentially increase the ability of a procedure to detect false null hypotheses in situations where one seeks to control k or more false rejections having tolerated a few of them. The k-FWER, which is the probability of at least k false rejections and generalizes the usual familywise error rat...
متن کاملAdaptive False Discovery Rate Control under Independence and Dependence
In the context of multiple hypothesis testing, the proportion π0 of true null hypotheses in the pool of hypotheses to test often plays a crucial role, although it is generally unknown a priori. A testing procedure using an implicit or explicit estimate of this quantity in order to improve its efficency is called adaptive. In this paper, we focus on the issue of false discovery rate (FDR) contro...
متن کاملAdaptive False Discovery Rate Control for Heterogeneous Data
Efforts to develop more efficient multiple hypothesis testing procedures for false discovery rate (FDR) control have focused on incorporating an estimate of the proportion of true null hypotheses (such procedures are called adaptive) or exploiting heterogeneity across tests via some optimal weighting scheme. This paper combines these approaches using a weighted adaptive multiple decision functi...
متن کاملPrivate False Discovery Rate Control
We provide the first differentially private algorithms for controlling the false discovery rate (FDR) in multiple hypothesis testing, with essentially no loss in power under certain conditions. Our general approach is to adapt a well-known variant of the Benjamini-Hochberg procedure (BHq), making each step differentially private. This destroys the classical proof of FDR control. To prove FDR co...
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: Electronic Journal of Statistics
سال: 2019
ISSN: 1935-7524
DOI: 10.1214/19-ejs1589