Selection of tuning parameters, solution paths and standard errors for Bayesian Lassos

DOI10.1214/16-BA1025zbMath1384.62102OpenAlexW2510752136MaRDI QIDQ1699685

Sounak Chakraborty, Vivekananda Roy

Publication date: 23 February 2018

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ba/1473276258

zbMATH Keywords

empirical Bayesimportance samplingMarkov chain Monte Carloshrinkagegeometric ergodicitystandard errorselastic netBayesian Lasso

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Bayesian inference (62F15) Discrete-time Markov processes on general state spaces (60J05)

Related Items (6)

Sparse Online Variational Bayesian Regression ⋮ \( \mathcal{G} \)-LIME: statistical learning for local interpretations of deep neural networks using global priors ⋮ Selection of Proposal Distributions for Multiple Importance Sampling ⋮ An exact sampler for fully Baysian elastic net ⋮ Bayesian MIDAS penalized regressions: estimation, selection, and prediction ⋮ Testing Sparsity-Inducing Penalties

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