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Everything about Bayesian multivariate linear regression
Bayesian approach to multivariate linear regression
In statistics, Bayesian multivariate linear regression is a Bayesian approach to multivariate linear regression, i.e. linear regression where the predicted outcome is a vector of correlated random variables rather than a single scalar random variable. A more general treatment of this approach can be found in the article MMSE estimator. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Bayesian multivariate linear regressionA 5-minute orientation
- Skim a recent paper: Bayesian joint relatively quantile regression of latent ordinal multivariate linear models with application to multirater agreement analysisInfluential work since 2022
- Pick up a classic book: Regression and Other StoriesThe most-reprinted book on the subject
- Read the landmark paper: Bayesian Robust Multivariate Linear Regression with Incomplete DataCited 83 times
- Go sideways: Bayesian linear regressionA closely related topic
- Go sideways: Gauss–Markov theoremA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Bayesian Robust Multivariate Linear Regression with Incomplete Data
Bayesian multivariate linear regression with application to change point models in hydrometeorological variables
Bayesian Regression with Multivariate Linear Splines
Bayesian linear regression for multivariate responses under group sparsity
Convergence Analysis of MCMC Algorithms for Bayesian Multivariate Linear Regression with Non‐Gaussian Errors
Trace-class Monte Carlo Markov chains for Bayesian multivariate linear regression with non-Gaussian errors
General Hyperplane Prior Distributions Based on Geometric Invariances for Bayesian Multivariate Linear Regression
Streamflow Simulation Using Bayesian Regression with Multivariate Linear Spline to Estimate Future Changes
🆕 Influential since 2022
Bayesian joint relatively quantile regression of latent ordinal multivariate linear models with application to multirater agreement analysis
Consistent Bayesian information criterion based on a mixture prior for possibly high‐dimensional multivariate linear regression models
Convergence analysis of data augmentation algorithms for Bayesian robust multivariate linear regression with incomplete data
Scalable Bayesian Inference on High-Dimensional Multivariate Linear Regression
📚 Books worth reading
Regression and Other StoriesAndrew Gelman, Jennifer Hill · 2020
Mathematical Statistics Theory and ApplicationsYu. A. Prokhorov, V. V. Sazonov · 2020
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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