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PUlasso  

High-Dimensional Variable Selection with Presence-Only Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PUlasso", "3.2.6")



Attach the package and use:
library("PUlasso")
Maintained by
Hyebin Song
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-12-13
Latest Update: 2023-12-18
Description:
Efficient algorithm for solving PU (Positive and Unlabeled) problem in low or high dimensional setting with lasso or group lasso penalty. The algorithm uses Maximization-Minorization and (block) coordinate descent. Sparse calculation and parallel computing are supported for the computational speed-up. See Hyebin Song, Garvesh Raskutti (2018) .
How to cite:
Hyebin Song (2017). PUlasso: High-Dimensional Variable Selection with Presence-Only Data. R package version 3.2.6, https://cran.r-project.org/web/packages/PUlasso. Accessed 04 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:16), 1.2 (2017-12-13 10:37), 2.1 (2018-01-03 14:49), 2.2 (2018-02-14 05:21), 3.1.1 (2018-05-15 07:46), 3.1 (2018-04-07 07:10), 3.2.2 (2019-02-28 18:40), 3.2.3 (2019-04-28 09:00), 3.2.4 (2021-01-17 06:50), 3.2.5 (2023-12-18 15:40)
Other packages that cited PUlasso R package
View PUlasso citation profile
Other R packages that PUlasso depends, imports, suggests or enhances
Complete documentation for PUlasso
Functions, R codes and Examples using the PUlasso R package
Full PUlasso package functions and examples
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