A testing based approach to the discovery of differentially correlated variable sets
From MaRDI portal
Publication:1624840
DOI10.1214/17-AOAS1083zbMath1405.62160arXiv1509.08124OpenAlexW2963340803WikidataQ92219804 ScholiaQ92219804MaRDI QIDQ1624840
Publication date: 16 November 2018
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1509.08124
Applications of statistics to biology and medical sciences; meta analysis (62P10) Measures of association (correlation, canonical correlation, etc.) (62H20) Biomedical imaging and signal processing (92C55) Protein sequences, DNA sequences (92D20)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A testing based extraction algorithm for identifying significant communities in networks
- Limiting laws of coherence of random matrices with applications to testing covariance structure and construction of compressed sensing matrices
- Optimal rates of convergence for covariance matrix estimation
- Covariance regularization by thresholding
- Flexible covariance estimation in graphical Gaussian models
- The asymptotic covariance matrix of sample correlation coefficients under general conditions
- The control of the false discovery rate in multiple testing under dependency.
- Modeling the Spatial and Temporal Dependence in fMRI Data
- A Factor Model Approach to Multiple Testing Under Dependence
- The asymptotic distribution of elements of a correlation matrix: Theory and application
- Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings
- Partial Correlation Estimation by Joint Sparse Regression Models
- Testing differential networks with applications to the detection of gene-gene interactions
This page was built for publication: A testing based approach to the discovery of differentially correlated variable sets