Package: ACSSpack 1.0.0.2

Ziqian Yang

ACSSpack: ACSS, Corresponding INSS, and GLP Algorithms

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, submitted to Journal of Business & Economic Statistics) "Bayesian methodology for adaptive sparsity and shrinkage in regression".

Authors:Ziqian Yang [cre, aut], Kshitij Khare [aut], George Michailidis [aut]

ACSSpack_1.0.0.2.tar.gz
ACSSpack_1.0.0.2.zip(r-4.7)ACSSpack_1.0.0.2.zip(r-4.6)ACSSpack_1.0.0.2.zip(r-4.5)
ACSSpack_1.0.0.2.tgz(r-4.6-x86_64)ACSSpack_1.0.0.2.tgz(r-4.6-arm64)ACSSpack_1.0.0.2.tgz(r-4.5-x86_64)ACSSpack_1.0.0.2.tgz(r-4.5-arm64)
ACSSpack_1.0.0.2.tar.gz(r-4.7-arm64)ACSSpack_1.0.0.2.tar.gz(r-4.7-x86_64)ACSSpack_1.0.0.2.tar.gz(r-4.6-arm64)ACSSpack_1.0.0.2.tar.gz(r-4.6-x86_64)
ACSSpack_1.0.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
ACSSpack/json (API)

# Install 'ACSSpack' in R:
install.packages('ACSSpack', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

archivedpackagesr-universeopenblascppopenmp

1.70 score 5 stars 208 downloads 3 exports 17 dependencies

Last updated from:d5313a5579 (on package/ACSSpack). Checks:13 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK137
linux-devel-x86_64OK124
source / vignettesOK182
linux-release-arm64OK155
linux-release-x86_64OK114
macos-release-arm64OK102
macos-release-x86_64OK162
macos-oldrel-arm64OK128
macos-oldrel-x86_64OK160
windows-develOK102
windows-releaseOK112
windows-oldrelOK109
wasm-releaseOK108

Exports:ACSS_gsGLP_gsINSS_gs

Dependencies:codetoolsdoParallelextraDistrforeachglmnetHDCIiteratorslatticeMASSMatrixmvtnormRcppRcppArmadilloRcppEigenshapeslamsurvival