On the proof of posterior contraction for sparse generalized linear models with multivariate responses
@inproceedings{Wang2022OnTP, title={On the proof of posterior contraction for sparse generalized linear models with multivariate responses}, author={Shao-Hsuan Wang and Ray Bai and Hsin-Hsiung Huang}, year={2022} }
In recent years, the literature on Bayesian high-dimensional variable selection has rapidly grown. It is increasingly important to understand whether these Bayesian methods can consistently estimate the model parameters. To this end, shrinkage priors are useful for identifying relevant signals in high-dimensional data. For multivariate linear regression models with Gaussian response variables, Bai and Ghosh (2018) [5] proposed a multivariate Bayesian model with shrinkage priors (MBSP) for…
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