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binsreg (version 0.2.0)

Binscatter Estimation and Inference

Description

Provides tools for statistical analysis using the binscatter methods developed by Cattaneo, Crump, Farrell and Feng (2019a) and Cattaneo, Crump, Farrell and Feng (2019b) . 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.

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Version

Install

install.packages('binsreg')

Monthly Downloads

870

Version

0.2.0

License

GPL-2

Maintainer

Yingjie Feng

Last Published

March 19th, 2019

Functions in binsreg (0.2.0)

binsreg

Data-driven Binscatter Estimation with Robust Inference Procedures and Plots
binsregselect

Data-driven IMSE-Optimal Partitioning/Binning Selection for Binscatter
print.CCFFbinsregtest

Internal function.
summary.CCFFbinsreg

Internal function.
print.CCFFbinsregselect

Internal function.
binsreg-package

Binsreg Package Document
summary.CCFFbinsregselect

Internal function.
summary.CCFFbinsregtest

Internal function.
print.CCFFbinsreg

Internal function.
binsregtest

Data-driven Nonparametric Shape Restriction and Parametric Model Specification Testing using Binscatter