High Dimensional Bayesian Ridge Regression without MCMC

Implements Bayesian ridge regression for high-dimensional data without using Markov chain Monte Carlo (MCMC). Posterior computations are performed using singular value decomposition (SVD) or QR decomposition. The package also provides variable selection and prediction methods.


Reference manual

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install.packages("HDBRR")

1.1.5 by Blanca Monroy-Castillo, 12 days ago


Browse source code at https://github.com/cran/HDBRR


Authors: Blanca Monroy-Castillo [aut, cre] , Paulino Perez-Rodriguez [ctb] , Jose Crossa [ctb] , Sergio Perez-Elizalde [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports numDeriv, parallel, bigparallelr, bigstatsr, graphics, stats


See at CRAN