HDMAADMM

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.

Last 30 days

This package has been downloaded 154 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.

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Last 365 days

This package has been downloaded 1,876 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 22 downloads.

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