Description Usage Arguments Details Value Author(s) Examples
Cross validation for choosing RMRCE tuning parameters
1 | RMRCE_cv(X, Y, lambdavec, alphavec)
|
X |
A numeric matrix of explanatory variables. |
Y |
A numeric vector of response. |
lambda |
A numeric vector of tuning parameter lambda for which the testing error is to be computed. |
alpha |
A numeric vector of tuning parameter alpha for which the testing error is to be computed. |
This function performs a five-fold cross validation to choose the optimal tuning parameters lambda and alpha which yield the smallest testing error.
A data.frame which has three columns: lambda, alpha and corresponding testing error. Lambda and alpha that yield the smallest testing error are selected as the optimal tuning parameters.
Fang Han, Hongkai Ji, Zhicheng Ji, Honglang Wang <zji4@jhu.edu>
1 2 3 4 5 6 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.