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smog  

Structural Modeling by using Overlapped Group Penalty
View on CRAN: Click here


Download and install smog package within the R console
Install from CRAN:
install.packages("smog")

Install from Github:
library("remotes")
install_github("cran/smog")

Install by package version:
library("remotes")
install_version("smog", "2.1.0")



Attach the package and use:
library("smog")
Maintained by
Chong Ma
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-20
Latest Update: 2024-01-12
Description:
Fits a linear non-penalized phenotype (demographic) variables and penalized groups of prognostic effect and predictive effect, by satisfying such hierarchy structures that if a predictive effect exists, its prognostic effect must also exist. This package can deal with continuous, binomial or multinomial, and survival response variables, underlying the assumption of Gaussian, binomial (multinomial), and Cox proportional hazard models, respectively. It is implemented by combining the iterative shrinkage-thresholding algorithm and the alternating direction method of multipliers algorithms. The main method is built in C++, and the complementary methods are written in R.
How to cite:
Chong Ma (2019). smog: Structural Modeling by using Overlapped Group Penalty. R package version 2.1.0, https://cran.r-project.org/web/packages/smog. Accessed 07 Nov. 2024.
Previous versions and publish date:
2.0 (2019-12-20 14:30), 2.1.0 (2020-08-10 18:50)
Other packages that cited smog R package
View smog citation profile
Other R packages that smog depends, imports, suggests or enhances
Functions, R codes and Examples using the smog R package
Some associated functions: cv.cglasso . cv.smog . glog . penalty . plot.cv.cglasso . plot.cv.smog . plot.smog . predict.smog . prox . proxL1 . proxL2 . sim_rct_biomarker . smog.default . smog . 
Some associated R codes: RcppExports.R . cv_cglasso.R . cv_smog.R . globals.R . sim_rct_biomarker.R . smog-package.R . smog.R . utility.R .  Full smog package functions and examples
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