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False discovery rate
Multiple Testing
Discussion: on Methods Controlling the False Discovery Rate
Inference on the Limiting False Discovery Rate and the P-Value Threshold Parameter Assuming Weak Dependence Between Gene Expression Levels Within Subject
Heterocedasticity-Adjusted Ranking and Thresholding for Large-Scale Multiple Testing
Comprehensive Comparative Analysis of Local False Discovery Rate Control Methods
Asymptotic Results on Adaptive False Discovery Rate Controlling Procedures Based on Kernel Estimators
1 Why Is Multiple Testing a Problem? 2 the Bonferroni Correction
False Discovery Rate 1 the Pairwise Multiple
Size, Power and False Discovery Rates
P and Q Values in RNA Seq the Q-Value Is an Adjusted P-Value, Taking in to Account the False Discovery Rate (FDR)
From P-Value to FDR
False Discovery Rate Control with Unknown Null Distribution: Is It Possible to Mimic the Oracle?
Principal Component Analysis for Big Data Arxiv:1801.01602V1 [Stat.ME
Controlling the Proportion of Falsely-Rejected Hypotheses When Conducting Multiple Tests with Climatological Data
Control of the False Discovery Rate Under Dependence Using the Bootstrap and Subsampling
Neuralfdr: Learning Discovery Thresholds from Hypothesis Features
"Principal Component Analysis for Big Data" In
Multtest: Resampling-Based Multiple Hypothesis Testing
Top View
Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate1
False Discovery Rate 1 the Pairwise Multiple Comparison
Control of the False Discovery Rate Under Dependence Using the Bootstrap and Subsampling
A Novel Principal Component Analysis Method for Identifying Differentially Expressed Gene Signatures Ai-Ling Teh Iowa State University
Scrutiny of the Monotone Likelihood Ratio Assumption in Multiple Testing
A Leave-P-Out Based Estimation of the Proportion of Null Hypotheses Alain Celisse, Stéphane Robin
Homework 1 Questions Model Selection and Evaluation of Results
Don't Have to Worry About Multiple Comparisons
False Discovery Rate Control
False Discovery Rate Computation: Illustrations and Modifications by Megan Hollister Murray and Jeffrey D
Effect of Cross-Validation on the Output of Multiple Testing Procedures Josh Dallas Price University of Arkansas, Fayetteville
Resampling-Based Control of the FDR
Estimation of the False Discovery Rate
SUPPLEMENTARY MATERIAL Method the False Discovery Rate (FDR) Method Offers an Objective Way to Select a P- Value Threshold That
Estimating False Discovery Proportion Under Arbitrary Covariance
Resampling-Based False Discovery Rate Controlling Multiple Test Procedures for Correlated Test Statistics
Miscellanea False Discovery Rate for Scanning Statistics
Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm
Asymptotic Properties of MSE Estimate for the False Discovery Rate Controlling Procedures in Multiple Hypothesis Testing
Controlling the False Discovery Rate in Two-Stage Combination Tests for Multiple Endpoints
Discovering the False Discovery Rate
Lecture 10: Multiple Testing Goals
Technical Analysis and Discrete False Discovery Rate: Evidence from MSCI Indices
Testing Significance of Features by Lassoed Principal Components
A Direct Approach to False Discovery Rates
Testing Multiple Hypotheses and False Discovery Rate Models, Inference, and Algorithms Primer
Adaptive False Discovery Rate Control for Heterogeneous Data
Multiple Comparisons: Bonferroni Corrections and False Discovery Rates
Estimating the Number of True Null Hypotheses and the False Discovery
Benjamini-Hochberg Procedure
False Discovery Rates
Controlling the Proportion of Falsely Rejected Hypotheses When Conducting Multiple Tests with Climatological Data