rlasso: Estimate treatment effect via the R-lasso, as proposed by Nie...
In swager/amlinear: Augmented Minmimax Linear Estimation
rlasso R Documentation
Estimate treatment effect via the R-lasso, as proposed by Nie and Wager (2017)
Description
Estimate treatment effect via the R-lasso, as proposed by Nie and Wager (2017)
Usage
rlasso(X, Y, W, alpha = 1, nfolds = NULL, lambda.choice = c("lambda.1se",
"lambda.min"), standardize = TRUE)
Arguments
X
the input features
Y
the observed response (real valued)
W
the effect variable (real valued)
alpha
tuning parameter for the elastic net
nfolds
number of folds for cross-fitting
lambda.choice
how to cross-validated
standardize
whether X should be rescaled before running the lasso
swager/amlinear documentation built on Aug. 30, 2023, 4:21 a.m.
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| rlasso | R Documentation |
Estimate treatment effect via the R-lasso, as proposed by Nie and Wager (2017)
Description
Estimate treatment effect via the R-lasso, as proposed by Nie and Wager (2017)
Usage
rlasso(X, Y, W, alpha = 1, nfolds = NULL, lambda.choice = c("lambda.1se",
"lambda.min"), standardize = TRUE)
Arguments
X |
the input features |
Y |
the observed response (real valued) |
W |
the effect variable (real valued) |
alpha |
tuning parameter for the elastic net |
nfolds |
number of folds for cross-fitting |
lambda.choice |
how to cross-validated |
standardize |
whether X should be rescaled before running the lasso |
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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