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mpath  

Regularized Linear Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mpath", "0.4-2.26")



Attach the package and use:
library("mpath")
Maintained by
Zhu Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-09-22
Latest Update: 2024-06-27
Description:
Algorithms compute robust estimators for loss functions in the concave convex (CC) family by the iteratively reweighted convex optimization (IRCO), an extension of the iteratively reweighted least squares (IRLS). The IRCO reduces the weight of the observation that leads to a large loss; it also provides weights to help identify outliers. Applications include robust (penalized) generalized linear models and robust support vector machines. The package also contains penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. Wang et al. (2014) , Wang et al. (2015) , Wang et al. (2016) , Wang (2021) , Wang (2024) .
How to cite:
Zhu Wang (2014). mpath: Regularized Linear Models. R package version 0.4-2.26, https://cran.r-project.org/web/packages/mpath. Accessed 02 Sep. 2026.
Previous versions and publish date:
(2026-07-12 23:50), 0.1-14 (2014-09-22 21:27), 0.1-15 (2014-09-23 17:37), 0.1-16 (2014-11-10 01:42), 0.1-17 (2014-11-10 23:05), 0.1-18 (2015-06-10 19:18), 0.1-19 (2015-07-23 17:14), 0.1-20 (2015-11-22 11:48), 0.2-1 (2016-02-05 00:29), 0.2-3 (2016-08-30 01:01), 0.2-4 (2016-08-30 19:22), 0.3-3 (2017-08-18 19:53), 0.3-4 (2017-10-23 20:18), 0.3-5 (2018-07-21 17:00), 0.3-6 (2019-01-14 21:00), 0.3-7 (2019-02-27 17:50), 0.3-12 (2019-04-15 09:42), 0.3-13 (2019-05-19 06:20), 0.3-15 (2019-06-06 00:10), 0.3-16 (2019-07-10 10:40), 0.3-17 (2019-08-01 23:30), 0.3-18 (2019-10-06 18:20), 0.3-19 (2019-11-08 00:00), 0.3-20 (2019-11-10 16:20), 0.3-21 (2020-01-10 06:30), 0.3-22 (2020-02-19 22:10), 0.3-23 (2020-02-20 08:00), 0.3-24 (2020-03-24 18:00), 0.3-25 (2020-04-22 23:44), 0.3-26 (2020-06-01 22:30), 0.4-2.16 (2020-11-10 23:20), 0.4-2.17 (2020-12-13 20:40), 0.4-2.18 (2021-02-15 22:20), 0.4-2.19 (2021-04-05 18:10), 0.4-2.20 (2021-12-03 23:20), 0.4-2.21 (2022-02-09 22:20), 0.4-2.22 (2022-02-22 01:40), 0.4-2.23 (2023-01-06 19:50), 0.4-2.25 (2024-03-09 21:10), 0.4-2.26 (2024-06-28 00:00)
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