Description Usage Arguments Examples
Cross validation for linear models with the lasso penalty
where n is the sample size and λ is a tuning parameter that controls the sparsity of β.
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x |
The design matrix |
y |
The response vector |
lambda |
A user provided sequence of λ. If set to
|
gamma |
bandwidth for MCP/SCAD |
type.measure |
measure to evaluate for cross-validation. The default is |
nfolds |
number of folds for cross-validation. default is 10. 3 is smallest value allowed. |
foldid |
an optional vector of values between 1 and nfold specifying which fold each observation belongs to. |
grouped |
Like in glmnet, this is an experimental argument, with default |
keep |
If |
parallel |
If TRUE, use parallel foreach to fit each fold. Must register parallel before hand, such as doMC. |
... |
other parameters to be passed to |
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