| Name : R-hdcate
| |
| Version : 0.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp156.6.1
| Date : 2024-09-10 03:41:25
|
| Group : Development/Libraries/Other
| Source RPM : R-hdcate-0.1.0-lp156.6.1.src.rpm
|
| Size : 0.29 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Estimation of Conditional Average Treatment Effects with High-Dimensional Data
|
Description :
A two-step double-robust method to estimate the conditional average
treatment effects (CATE) with potentially high-dimensional
covariate(s). In the first stage, the nuisance functions necessary for
identifying CATE are estimated by machine learning methods, allowing
the number of covariates to be comparable to or larger than the sample
size. The second stage consists of a low-dimensional local linear
regression, reducing CATE to a function of the covariate(s) of
interest. The CATE estimator implemented in this package not only
allows for high-dimensional data, but also has the “double robustness”
property: either the model for the propensity score or the models for
the conditional means of the potential outcomes are allowed to be
misspecified (but not both). This package is based on the paper by Fan
et al., \"Estimation of Conditional Average Treatment Effects With
High-Dimensional Data\" (2022), Journal of Business & Economic
Statistics < doi:10.1080/07350015.2020.1811102>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.6/x86_64 |
