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smog
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]
[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
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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