CRAN/E | HDMAADMM

HDMAADMM

ADMM for High-Dimensional Mediation Models

Installation

About

We use the Alternating Direction Method of Multipliers (ADMM) for parameter estimation in high-dimensional, single-modality mediation models. To improve the sensitivity and specificity of estimated mediation effects, we offer the sure independence screening (SIS) function for dimension reduction. The available penalty options include Lasso, Elastic Net, Pathway Lasso, and Network-constrained Penalty. The methods employed in the package are based on Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011). doi:10.1561/2200000016, Fan, J., & Lv, J. (2008) doi:10.1111/j.1467-9868.2008.00674.x, Li, C., & Li, H. (2008) doi:10.1093/bioinformatics/btn081, Tibshirani, R. (1996) doi:10.1111/j.2517-6161.1996.tb02080.x, Zhao, Y., & Luo, X. (2022) doi:10.4310/21-sii673, and Zou, H., & Hastie, T. (2005) doi:10.1111/j.1467-9868.2005.00503.x.

github.com/psyen0824/HDMAADMM
Bug report File report

Key Metrics

Version 0.0.1
R ≥ 4.0.0
Published 2023-11-29 157 days ago
Needs compilation? yes
License MIT
License File
CRAN checks HDMAADMM results

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Maintainer

Maintainer

Pei-Shan Yen

peishan0824@gmail.com

Authors

Pei-Shan Yen

aut / cre

Ching-Chuan Chen

aut

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 4.0.0

Imports

Rcpp ≥ 1.0.0
dqrng
RcppEigen

Suggests

roxygen2

LinkingTo

Rcpp
RcppEigen