Sparse basis covariance matrix estimation for high dimensional compositional data via hard thresholding
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Publication:6569427
DOI10.1016/j.spl.2024.110088zbMATH Open1541.62128MaRDI QIDQ6569427
Publication date: 9 July 2024
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
upper boundcompositional dataprobability estimationhard thresholding estimatorsparse basis covariance matrix
Estimation in multivariate analysis (62H12) Design of statistical experiments (62K99) Parametric inference under constraints (62F30) Analysis of variance and covariance (ANOVA) (62J10)
Cites Work
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- Optimal rates of convergence for sparse covariance matrix estimation
- Covariance regularization by thresholding
- Minimax estimation of covariance and precision matrices for high-dimensional time series with long-memory
- Estimation of large covariance and precision matrices from temporally dependent observations
- Positive definite estimators of large covariance matrices
- Adaptive Thresholding for Sparse Covariance Matrix Estimation
- Large Covariance Estimation for Compositional Data Via Composition-Adjusted Thresholding
- Robust estimation of high-dimensional covariance and precision matrices
- Robust Shape Matrix Estimation for High-Dimensional Compositional Data with Application to Microbial Inter-Taxa Analysis
- Sparse covariance matrix estimation for ultrahigh dimensional data
- Robust covariance estimation for high-dimensional compositional data with application to microbial communities analysis
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