Package: RegCombin 0.4.1

Christophe Gaillac

RegCombin: 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) <doi:10.3386/w29953>. 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.

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

RegCombin_0.4.1.tar.gz
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RegCombin.pdf |RegCombin.html✨
RegCombin/json (API)

# Install 'RegCombin' in R:
install.packages('RegCombin', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5 exports 1 stars 0.09 score 84 dependencies 211 downloads

Last updated 11 months agofrom:12e2130cc6. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-linuxOKSep 10 2024

Exports:DGM_boundspoint_ident_testregCombinregCombin_profilesummary_regCombin

Dependencies:abindbackportsbase64encbslibcachemcheckmatecliclustercolorspacecpp11data.tabledigestdplyrevaluatefansifarverfastmapfontawesomeforeignFormulafsgenericsgeometryggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonlitekableExtraknitrlabelinglatticelifecyclelinproglpSolvemagicmagrittrMASSMatrixmemoisemgcvmimemunsellnlmennetpillarpkgconfigpracmaR6rappdirsRationalExpRColorBrewerRcppRcppProgressrlangrmarkdownrpartrstudioapisassscalessnowsnowfallstringistringrsvglitesystemfontstibbletidyselecttinytexutf8vctrsviridisviridisLitewithrxfunxml2yaml

Readme and manuals

Help Manual

Help pageTopics
This function finds the boundary of the identified set in one specified direction using the AS test and Newton's method.AS_bounds
This function computes the AS test using DGM implementation in the package RationalExpAStest
Function to compute the bounds on the coefficients of the common regressors.compute_bnds_betac
Compute the indexes of the values of the common regressors Xc used in the various shape constraintscompute_constraints
Function to compute the DGM bounds on the noncommon regressor Xnccompute_radial
Function to compute the DGM bounds on the noncommon regressor Xnc, adapted to the point identification test.compute_radial_test
Function to compute the main statistic for the point estimatecompute_ratio
Function to compute the variance boundscompute_ratio_variance
Function to compute the Variance bounds on the noncommon regressor Xnccompute_stat_variance
Compute the support function for the projections of the identified setcompute_support
Function to minimize to compute the function sigma for the projections of the identified setcompute_support_paral
Function to create the matrix of the support points for the common regressors Xccreate_values
This function compute the DGM bounds for all the different coefficients.DGM_bounds
This function compute the DGM bounds for all the different coefficients, adapted to the point identification test.DGM_bounds_test
Compute the weighted empirical cumulative distributionewcdf
Internal function to minimize to compute the function sigma for the projections of the identified setobjective_support
Function performing the test of point identification on a validation sample.point_ident_test
Function computing all the different bounds : DGM and/or VarianceregCombin
Computing the DGM bounds for different values of epsilon, proportional to the data-driven selected oneregCombin_profile
The subsampling rulesampling_rule
Function for the data-driven selection of the epsilon tuning parameterselect_epsilon
Function for the data-driven selection of the epsilon tuning parameter, adapted to the point identification test.select_epsilon_test
Produce the final summary table for the output of the felogit functionsummary_regCombin
Function to tabulate the values the common regressors Xc whatever the dimension.tabulate_values
Function to compute the variance bounds for XncVariance_bounds