Partially Linear Regression under Data Combination

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 < https://github.com/cgaillac/RegCombin/blob/master/RegCombin_vignette.pdf> for theory and code examples.


Reference manual

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install.packages("RegCombin")

0.4.1 by Christophe Gaillac, 3 years ago


Browse source code at https://github.com/cran/RegCombin


Authors: Xavier D'Haultfoeuille [aut] , Christophe Gaillac [aut, cre] , Arnaud Maurel [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports dplyr, kableExtra, snowfall, RationalExp, Hmisc, geometry, pracma

Suggests knitr, rmarkdown


See at CRAN