ACSSpack: ACSS, Corresponding ACSS, and GLP Algorithm

Allow user to run the Adaptive Correlated Spike and Slab (ACSS) algorithm, corresponding INdependent Spike and Slab (INSS) algorithm, and Giannone, Lenza and Primiceri (GLP) algorithm with adaptive burn-in. All of the three algorithms are used to fit high dimensional data set with either sparse structure, or dense structure with smaller contributions from all predictors. The state-of-the-art GLP algorithm is in Giannone, D., Lenza, M., & Primiceri, G. E. (2021, ISBN:978-92-899-4542-4) "Economic predictions with big data: The illusion of sparsity". The two new algorithms, ACSS algorithm and INSS algorithm, and the discussion on their performance can be seen in Yang, Z., Khare, K., & Michailidis, G. (2024, preprint) "Bayesian methodology for adaptive sparsity and shrinkage in regression".

Getting started

Package details

AuthorZiqian Yang [cre, aut], Kshitij Khare [aut], George Michailidis [aut]
MaintainerZiqian Yang <zi.yang@ufl.edu>
LicenseGPL-3
Version0.0.1.4
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("ACSSpack")

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ACSSpack documentation built on July 4, 2024, 5:07 p.m.