grpregPredict: Predictions on Test Data with Grpreg
In bestglm: Best Subset GLM and Regression Utilities
Description
Usage
Arguments
Value
See Also
Examples
View source: R/grpregPredict.R
Description
A dataframe is partitioned randomly into training and test samples.
The function grpreg::grpreg() is used to fit the training data
using Lasso, SCAD and MCP penalty functions. The BIC criterion is used
to selecting the penalty parameter lambda.
Usage
1
grpregPredict(Xy, trainFrac = 2/3, XyList=NULL)
Arguments
Xy
a dataframe that may contain factor variables
trainFrac
the fraction of data to be used for training
XyList
instead of supplying Xy you can provide XyList.
Value
vector of RMSEs
See Also
glmnetPredict,
glmnetGridTable,
trainTestPartition,
grpreg
Examples
1
bestglm documentation built on March 26, 2020, 7:25 p.m.
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Description Usage Arguments Value See Also Examples
View source: R/grpregPredict.R
Description
A dataframe is partitioned randomly into training and test samples. The function grpreg::grpreg() is used to fit the training data using Lasso, SCAD and MCP penalty functions. The BIC criterion is used to selecting the penalty parameter lambda.
Usage
1 | grpregPredict(Xy, trainFrac = 2/3, XyList=NULL)
|
Arguments
Xy |
a dataframe that may contain factor variables |
trainFrac |
the fraction of data to be used for training |
XyList |
instead of supplying Xy you can provide XyList. |
Value
vector of RMSEs
See Also
glmnetPredict,
glmnetGridTable,
trainTestPartition,
grpreg
Examples
1 |
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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