Description Usage Arguments Examples
OWL and RWL are benchmark models in our simulation study
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H: |
n by P feature matrix |
A: |
treatment, takes value -1 and +1 with size n |
R2: |
outcome or residual vector with length n |
pi: |
propensity score with length n |
pentype: |
penalty in the residual estimation process, useful or RWL only |
kernel: |
kernel used in SVM |
residual: |
True or False, if True then RWL is deployed, if FALSE then OWL is deployed. Default is True. |
sigma: |
hyper-parameter in SVM rbf kernel |
clinear: |
hyper-parameter in SVM rbf kernel |
m: |
number of fold for cross validation in parameter tunning |
e: |
least tolerated error |
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