Bayesian adaptive Lasso estimation of large graphical model based on modified Cholesky decomposition

Fanqun Li, Mingtao Zhao and Kongsheng Zhang

Statistics & Probability Letters, 2024, vol. 206, issue C

Abstract: In this paper, based on the modified Cholesky decomposition of the precision matrix, we propose Bayesian adaptive Lasso estimation and maximum adaptive posterior estimation for graphical model. We also recover the graph by minimizing the decoupled shrinkage and selection loss function.

Keywords: Graphical model; Regression; Bayesian adaptive Lasso; Modified Cholesky decomposition (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.spl.2023.110004

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