Package: binsreg
Type: Package
Title: Binscatter Estimation and Inference
Date: 2019-03-17
Version: 0.2.0
Author: Matias D. Cattaneo, Richard K. Crump, Max H. Farrell, Yingjie Feng
Maintainer: Yingjie Feng <yjfeng@umich.edu>
Description: 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.
Depends: R (>= 3.1)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: ggplot2, sandwich
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-18 02:36:38 UTC; Yingjie
Repository: CRAN
Date/Publication: 2019-03-19 15:03:25 UTC
