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binsreg  

Binscatter Estimation and Inference
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("binsreg", "1.1")



Attach the package and use:
library("binsreg")
Maintained by
Yingjie Feng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-03-19
Latest Update: 2024-07-23
Description:
Provides tools for statistical analysis using the binscatter methods developed by Cattaneo, Crump, Farrell and Feng (2023a) , Cattaneo, Crump, Farrell and Feng (2023b) and Cattaneo, Crump, Farrell and Feng (2023c) . Binscatter provides a flexible way of describing the relationship between two variables based on partitioning/binning of the independent variable of interest. binsreg(), binsqreg() and binsglm() implement binscatter least squares regression, quantile regression and generalized linear regression respectively, with particular focus on constructing binned scatter plots. They also implement robust (pointwise and uniform) inference of regression functions and derivatives thereof. binstest() implements hypothesis testing procedures for parametric functional forms of and nonparametric shape restrictions on the regression function. binspwc() implements hypothesis testing procedures for pairwise group comparison of binscatter estimators. binsregselect() implements data-driven procedures for selecting the number of bins for binscatter estimation. All the commands allow for covariate adjustment, smoothness restrictions and clustering.
How to cite:
Yingjie Feng (2019). binsreg: Binscatter Estimation and Inference. R package version 1.1, https://cran.r-project.org/web/packages/binsreg. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:22), 0.2.0 (2019-03-19 16:03), 0.6 (2021-08-07 10:20), 0.7 (2021-10-11 06:40), 0.9 (2023-01-06 10:10), 1.0 (2023-07-11 14:00), 1.1 (2024-07-23 16:30), 2.0 (2026-05-15 18:00)
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