Sparse Laplacian Shrinkage with the Graphical Lasso Estimator for Regression Problems
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DOI: 10.1007/s11749-021-00779-7
Abstract: This paper considers a high-dimensional linear regression problem where there are complex correlation structures among predictors. We propose a graph-constrained regularization procedure, named Sparse Laplacian Shrinkage with the Graphical Lasso Estimator (SLS-GLE). The procedure uses… read more here.
Keywords: regression; lasso estimator; graphical lasso; laplacian shrinkage ... See more keywords
A Network-Based Comparison Between Molecular Apocrine Breast Cancer Tumor and Basal and Luminal Tumors by Joint Graphical Lasso
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DOI: 10.1109/tcbb.2019.2911074
Abstract: Joint graphical lasso (JGL) approach is a Gaussian graphical model to estimate multiple graphical models corresponding to distinct but related groups. Molecular apocrine (MA) breast cancer tumor has similar characteristics to luminal and basal subtypes.… read more here.
Keywords: molecular apocrine; joint graphical; graphical lasso; apocrine breast ... See more keywords
An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning
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DOI: 10.3389/fgene.2021.760299
Abstract: Biological networks are often inferred through Gaussian graphical models (GGMs) using gene or protein expression data only. GGMs identify conditional dependence by estimating a precision matrix between genes or proteins. However, conventional GGM approaches often… read more here.
Keywords: lasso; augmented high; method; network ... See more keywords