Science Score: 13.0%
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○Scientific vocabulary similarity
Low similarity (3.8%) to scientific vocabulary
Repository
An R package of MTE
Basic Info
- Host: GitHub
- Owner: shaobo-li
- Language: R
- Default Branch: master
- Size: 31.3 KB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
MTE: Maximum Tangent Likelihood Estimation
Overview
The package provides several robust estimation methods for linear regression under both fixed and high dimesional settings. The methods include Maximum Tangent Likelihood Estimator (MTE and MTElasso) (Qin et al., 2017+), Least Absolute Deviance Estimator (LAD and LADlasso) and Huber estimator (huber.reg and huber.lasso).
Installation
r
devtools::install_github("shaobo-li/MTE")
Example
r
library(MTE)
set.seed(2017)
n=200; d=500
X=matrix(rnorm(n*d), nrow=n, ncol=d)
beta=c(rep(2,6), rep(0, d-6))
y=X%*%beta+c(rnorm(150), rnorm(30,10,10), rnorm(20,0,100))
output.MTELasso=MTElasso(X, y, p=2, t=0.01)
beta.est=output.MTELasso$beta
References
Qin, Y., Li, S., Li, Y., & Yu, Y. (2017). Penalized maximum tangent likelihood estimation and robust variable selection. doi:10.48550/arXiv.1708.05439.
Owner
- Name: Shaobo Li
- Login: shaobo-li
- Kind: user
- Company: University of Kansas
- Repositories: 2
- Profile: https://github.com/shaobo-li
GitHub Events
Total
- Watch event: 1
- Push event: 1
Last Year
- Watch event: 1
- Push event: 1
Packages
- Total packages: 1
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Total downloads:
- cran 385 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 5
- Total maintainers: 1
cran.r-project.org: MTE
Maximum Tangent Likelihood Estimation for Robust Linear Regression and Variable Selection
- Homepage: https://github.com/shaobo-li/MTE
- Documentation: http://cran.r-project.org/web/packages/MTE/MTE.pdf
- License: GPL-3
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Latest release: 1.2.1
published about 1 year ago