glmtlp-package: Truncated lasso model paths for some generalized linear...
In ChongWu-Biostat/glmtlp: Truncated Lasso Regularized Generalized Linear Models
Description
Details
Author(s)
References
Description
This package fits truncated lasso based model paths for regression, logistic and multinomial regression using difference convex technique and coordinate descent. The algorithm is extremely fast, and exploits sparsity in the input x matrix where it exists. A variety of predictions can be made from the fitted models.
Details
Package: glmtlp
Type: Package
Version: 1.1
Date: 2018-02-01
License: GPL-2
Very simple to use. Accepts x,y data for regression models, and
produces the regularization path over a grid of values for the tuning
parameter lambda and tau. Only 5 functions:
glmtlp
predict.glmnet
plot.glmnet
print.glmnet
coef.glmnet
Author(s)
Chong Wu, Wei Pan
Maintainer: Chong Wu <wuxx0845@umn.edu>
References
Xiaotong Shen , Wei Pan and Yunzhang Zhu (2012)
Likelihood-Based Selection and Sharp Parameter Estimation,
Journal of the American Statistical Association, 107:497, 223-232
ChongWu-Biostat/glmtlp documentation built on May 6, 2019, 11:18 a.m.
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Description Details Author(s) References
Description
This package fits truncated lasso based model paths for regression, logistic and multinomial regression using difference convex technique and coordinate descent. The algorithm is extremely fast, and exploits sparsity in the input x matrix where it exists. A variety of predictions can be made from the fitted models.
Details
| Package: | glmtlp |
| Type: | Package |
| Version: | 1.1 |
| Date: | 2018-02-01 |
| License: | GPL-2 |
Very simple to use. Accepts x,y data for regression models, and
produces the regularization path over a grid of values for the tuning
parameter lambda and tau. Only 5 functions:
glmtlp
predict.glmnet
plot.glmnet
print.glmnet
coef.glmnet
Author(s)
Chong Wu, Wei Pan
Maintainer: Chong Wu <wuxx0845@umn.edu>
References
Xiaotong Shen , Wei Pan and Yunzhang Zhu (2012)
Likelihood-Based Selection and Sharp Parameter Estimation,
Journal of the American Statistical Association, 107:497, 223-232
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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