A mixture of g-priors for variable selection when the number of regressors grows with the sample size

Title
A mixture of g-priors for variable selection when the number of regressors grows with the sample size
Authors
Keywords
Model selection consistency, Misspecified models, General class of distributions of errors, Kullback–Leibler divergence, 62F15 Bayesian inference, 62F12 Asymptotic properties of estimators
Journal
TEST
Volume 26, Issue 2, Pages 377-404
Publisher
Springer Nature
Online
2016-12-20
DOI
10.1007/s11749-016-0516-0

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