cvDesparse: Select the optimal tuning for bootstrap-calibrated...
In WaverlyWei/subDebiased: Sharp Inference on Selected Subgroup in Observational Studies
cvDesparse R Documentation
Select the optimal tuning for bootstrap-calibrated desparsified Lasso
Description
Select the optimal tuning for bootstrap-calibrated desparsified Lasso
Usage
cvDesparse(y, x, r = NULL, G = NULL, B = NULL, fold = 3)
Arguments
y
response
x
design matrix
r
candidate tuning parameters
G
indices of subgroups
B
bootstrap repetitions
fold
number of folds in cross-validation
Value
op
optimal tuning parameter
WaverlyWei/subDebiased documentation built on June 30, 2022, 10:50 a.m.
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| cvDesparse | R Documentation |
Select the optimal tuning for bootstrap-calibrated desparsified Lasso
Description
Select the optimal tuning for bootstrap-calibrated desparsified Lasso
Usage
cvDesparse(y, x, r = NULL, G = NULL, B = NULL, fold = 3)
Arguments
y |
response |
x |
design matrix |
r |
candidate tuning parameters |
G |
indices of subgroups |
B |
bootstrap repetitions |
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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