Skip to main navigation
Skip to search
Skip to main content
Experts@Minnesota Home
Home
Profiles
Research units
University Assets
Projects and Grants
Research output
Press/Media
Datasets
Activities
Fellowships, Honors, and Prizes
Search by expertise, name or affiliation
On the geometric modeling approach to empirical null distribution estimation for empirical Bayes modeling of multiple hypothesis testing
Baolin Wu
Biostatistics
Research output
:
Contribution to journal
›
Article
›
peer-review
2
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'On the geometric modeling approach to empirical null distribution estimation for empirical Bayes modeling of multiple hypothesis testing'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Geometric Modeling
100%
Modeling Approach
100%
Multiple Testing
100%
Empirical Bayes
100%
Bayes Model
100%
Distribution Estimation
100%
Empirical null
100%
Non-parametric Approach
33%
Strong Dependence
33%
Poisson Regression
33%
Competitive Performance
33%
Test Statistic
33%
Microarray Data
33%
Null Distribution
33%
Finite Mixture Model
33%
Mathematics
Statistical Hypothesis Testing
100%
Modeling Approach
100%
Empirical Bayes Procedure
100%
Geometric Modeling
100%
Null
100%
Test Statistic
33%
Finite Mixture Model
33%
Poisson Regression
33%