Testing Jumps via False Discovery Rate Control
نویسندگان
چکیده
منابع مشابه
Testing Jumps via False Discovery Rate Control
Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such situation becomes even worse when the jump occurrence is a rare event. To obtain more reliable results, we aim to control the false discovery rat...
متن کاملFalse Discovery Rate Control via Debiased Lasso
We consider the problem of variable selection in high-dimensional statistical models where the goal is to report a set of variables, out of many predictors X1, . . . , Xp, that are relevant to a response of interest. For linear high-dimensional model, where the number of parameters exceeds the number of samples (p > n), we propose a procedure for variables selection and prove that it controls t...
متن کاملWeighted False Discovery Rate Control in Large-Scale Multiple Testing
The use of weights provides an effective strategy to incorporate prior domain knowledge in large-scale inference. This paper studies weighted multiple testing in a decisiontheoretic framework. We develop oracle and data-driven procedures that aim to maximize the expected number of true positives subject to a constraint on the weighted false discovery rate. The asymptotic validity and optimality...
متن کاملThe False Discovery Rate in Simultaneous Fisher and Adjusted Permutation Hypothesis Testing on Microarray Data
Background and Objectives: In recent years, new technologies have led to produce a large amount of data and in the field of biology, microarray technology has also dramatically developed. Meanwhile, the Fisher test is used to compare the control group with two or more experimental groups and also to detect the differentially expressed genes. In this study, the false discovery rate was investiga...
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: SSRN Electronic Journal
سال: 2011
ISSN: 1556-5068
DOI: 10.2139/ssrn.1586281