msaenet.tune.glmnet: Automatic (parallel) parameter tuning for glmnet models
In msaenet: Multi-Step Adaptive Estimation Methods for Sparse Regressions
Description
Usage
Value
Author(s)
References
View source: R/msaenet-tune-glmnet.R
Description
Automatic (parallel) parameter tuning for glmnet models
Usage
1
2
msaenet.tune.glmnet(x, y, family, alphas, tune, nfolds, rule, ebic.gamma,
lower.limits, upper.limits, seed, parallel, ...)
Value
Optimal model object, parameter set, and criterion value
Author(s)
Nan Xiao <https://nanx.me>
References
Chen, Jiahua, and Zehua Chen. (2008).
Extended Bayesian information criteria for model selection with
large model spaces. Biometrika 95(3), 759–771.
msaenet documentation built on May 18, 2019, 1:03 a.m.
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Description Usage Value Author(s) References
View source: R/msaenet-tune-glmnet.R
Description
Automatic (parallel) parameter tuning for glmnet models
Usage
1 2 | msaenet.tune.glmnet(x, y, family, alphas, tune, nfolds, rule, ebic.gamma,
lower.limits, upper.limits, seed, parallel, ...)
|
Value
Optimal model object, parameter set, and criterion value
Author(s)
Nan Xiao <https://nanx.me>
References
Chen, Jiahua, and Zehua Chen. (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika 95(3), 759–771.
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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