binsreg: Binscatter Estimation and Inference

Provides tools for statistical analysis using the binscatter methods developed by Cattaneo, Crump, Farrell and Feng (2019a) <arXiv:1902.09608> and Cattaneo, Crump, Farrell and Feng (2019b) <arXiv:1902.09615>. Binscatter provides a flexible way of describing the mean relationship between two variables based on partitioning/binning of the independent variable of interest. binsreg() implements binscatter estimation and robust (pointwise and uniform) inference of regression functions and derivatives thereof, with particular focus on constructing binned scatter plots. binsregtest() implements hypothesis testing procedures for parametric functional forms of and nonparametric shape restrictions on the regression function. 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.

Version: 0.2.0
Depends: R (≥ 3.1)
Imports: ggplot2, sandwich
Published: 2019-03-19
Author: Matias D. Cattaneo, Richard K. Crump, Max H. Farrell, Yingjie Feng
Maintainer: Yingjie Feng <yjfeng at umich.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: binsreg results

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Reference manual: binsreg.pdf
Package source: binsreg_0.2.0.tar.gz
Windows binaries: r-devel: binsreg_0.2.0.zip, r-release: binsreg_0.2.0.zip, r-oldrel: binsreg_0.2.0.zip
macOS binaries: r-release: binsreg_0.2.0.tgz, r-oldrel: binsreg_0.2.0.tgz

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