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hdcate
View on CRAN: Click
here
Download and install hdcate package within the R console
Install from CRAN:
install.packages("hdcate")
Install from Github:
library("remotes")
install_github("cran/hdcate")
Install by package version:
library("remotes")
install_version("hdcate", "0.1.0")
Attach the package and use:
library("hdcate")
Maintained by
Qingliang Fan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-14
Latest Update: 2022-12-14
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
How to cite:
Qingliang Fan (2022). hdcate: Estimation of Conditional Average Treatment Effects with High-Dimensional Data. R package version 0.1.0, https://cran.r-project.org/web/packages/hdcate. Accessed 29 Mar. 2025.
Previous versions and publish date:
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Complete documentation for hdcate
Functions, R codes and Examples using
the hdcate R package
Some associated functions: HDCATE.fit . HDCATE.get_sim_data . HDCATE.inference . HDCATE . HDCATE.plot . HDCATE.set_bw . HDCATE.set_condition_var . HDCATE.set_first_stage . HDCATE.unset_first_stage . HDCATE.use_cross_fitting . HDCATE.use_full_sample . HDCATE_R6Class .
Some associated R codes: hdcate_config_operators.R . hdcate_main_operators.R . hdcate_r6_class.R . simulation_data.R . Full hdcate package functions and examples
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