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RegCombin  

Partially Linear Regression under Data Combination
View on CRAN: Click here


Download and install RegCombin package within the R console
Install from CRAN:
install.packages("RegCombin")

Install from Github:
library("remotes")
install_github("cran/RegCombin")

Install by package version:
library("remotes")
install_version("RegCombin", "0.4.1")



Attach the package and use:
library("RegCombin")
Maintained by
Christophe Gaillac
[Scholar Profile | Author Map]
First Published: 2023-03-01
Latest Update: 2023-10-16
Description:
We implement linear regression when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked, based on D'Haultfoeuille, Gaillac, Maurel (2022) . The package allows for common regressors observed in both datasets, and for various shape constraints on the effect of covariates on the outcome of interest. It also provides the tools to perform a test of point identification. See the associated vignette for theory and code examples.
How to cite:
Christophe Gaillac (2023). RegCombin: Partially Linear Regression under Data Combination. R package version 0.4.1, https://cran.r-project.org/web/packages/RegCombin. Accessed 17 Feb. 2025.
Previous versions and publish date:
0.2.1 (2023-03-01 21:00), 0.3.1 (2023-09-07 19:00)
Other packages that cited RegCombin R package
View RegCombin citation profile
Other R packages that RegCombin depends, imports, suggests or enhances
Complete documentation for RegCombin
Functions, R codes and Examples using the RegCombin R package
Full RegCombin package functions and examples
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