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APML0
View on CRAN: Click
here
Download and install APML0 package within the R console
Install from CRAN:
install.packages("APML0")
Install from Github:
library("remotes")
install_github("cran/APML0")
Install by package version:
library("remotes")
install_version("APML0", "0.10")
Attach the package and use:
library("APML0")
Maintained by
Xiang Li
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-07-17
Latest Update: 2020-01-19
Description:
Fit linear, logistic and Cox models regularized with L0, lasso (L1), elastic-net (L1 and L2), or net (L1 and Laplacian) penalty, and their adaptive forms, such as adaptive lasso / elastic-net and net adjusting for signs of linked coefficients. It solves L0 penalty problem by simultaneously selecting regularization parameters and performing hard-thresholding or selecting number of non-zeros. This augmented and penalized minimization method provides an approximation solution to the L0 penalty problem, but runs as fast as L1 regularization problem. The package uses one-step coordinate descent algorithm and runs extremely fast by taking into account the sparsity structure of coefficients. It could deal with very high dimensional data and has superior selection performance.
How to cite:
Xiang Li (2017). APML0: Augmented and Penalized Minimization Method L0. R package version 0.10, https://cran.r-project.org/web/packages/APML0. Accessed 21 Nov. 2024.
Previous versions and publish date:
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Other R packages that APML0 depends,
imports, suggests or enhances
Functions, R codes and Examples using
the APML0 R package
Some associated functions: APML0-package . APML0 . print.APML0 .
Some associated R codes: APML0.R . RcppExports.R . net_cox.R . net_lm.R . net_logit.R . print.APML0.R . Full APML0 package functions and examples
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