cvSplit: Select the optimal tuning for bootstrap-calibrated R-Split...
In WaverlyWei/debiased.subgroup: Sharp Inference on Selected Subgroup in Observational Studies
cvSplit R Documentation
Select the optimal tuning for bootstrap-calibrated R-Split through cross-validation
Description
Select the optimal tuning for bootstrap-calibrated R-Split through cross-validation
Usage
cvSplit(y, x, r = NULL, G = NULL, B = NULL, BB = NULL, ratio = NULL, fold = 2)
Arguments
y
response
x
design matrix
r
candidate tuning parameter
G
subgroup indicator
B
bootstrap iterations
BB
bootstrap iterations for repetitive splitting
ratio
ratio of data splitting
fold
number of folds in cross-validation
Value
op
optimal tuning parameter
WaverlyWei/debiased.subgroup documentation built on June 27, 2022, 7:22 p.m.
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| cvSplit | R Documentation |
Select the optimal tuning for bootstrap-calibrated R-Split through cross-validation
Description
Select the optimal tuning for bootstrap-calibrated R-Split through cross-validation
Usage
cvSplit(y, x, r = NULL, G = NULL, B = NULL, BB = NULL, ratio = NULL, fold = 2)
Arguments
y |
response |
x |
design matrix |
r |
candidate tuning parameter |
G |
subgroup indicator |
B |
bootstrap iterations |
BB |
bootstrap iterations for repetitive splitting |
ratio |
ratio of data splitting |
fold |
number of folds in cross-validation |
Value
op |
optimal tuning parameter |
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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