nprobust: Kernel Density and Local Polynomial Regression Methods

Estimation, inference, bandwidth selection, and graphical procedures for kernel density and local polynomial regression methods, including robust bias-corrected confidence intervals as described in Calonico, Cattaneo and Farrell (2018, <doi:10.1080/01621459.2017.1285776>). The package includes 'lprobust()' for local polynomial point estimation and robust bias-corrected inference, 'lpbwselect()' for local polynomial bandwidth selection, 'kdrobust()' for kernel density point estimation and robust bias-corrected inference, 'kdbwselect()' for kernel density bandwidth selection, and 'nprobust.plot()' for plotting results. The main methodological and numerical features are described in Calonico, Cattaneo and Farrell (2019, <doi:10.18637/jss.v091.i08>).

Version:	1.0.0
Depends:	R (≥ 3.6.0)
Imports:	ggplot2
Suggests:	testthat (≥ 3.0.0), broom, sandwich
Published:	2026-05-19
DOI:	10.32614/CRAN.package.nprobust
Author:	Sebastian Calonico [aut, cre], Matias D. Cattaneo [aut], Max H. Farrell [aut]
Maintainer:	Sebastian Calonico <scalonico at ucdavis.edu>
BugReports:	https://github.com/nppackages/nprobust/issues
License:	GPL-3
URL:	https://github.com/nppackages/nprobust
NeedsCompilation:	no
Citation:	nprobust citation info
Materials:	README
CRAN checks:	nprobust results

Documentation:

Reference manual:

nprobust.html , nprobust.pdf

Downloads:

Package source:	nprobust_1.0.0.tar.gz
Windows binaries:	r-devel: nprobust_0.5.0.zip, r-release: nprobust_1.0.0.zip, r-oldrel: nprobust_1.0.0.zip
macOS binaries:	r-release (arm64): nprobust_1.0.0.tgz, r-oldrel (arm64): nprobust_1.0.0.tgz, r-release (x86_64): nprobust_1.0.0.tgz, r-oldrel (x86_64): nprobust_1.0.0.tgz
Old sources:	nprobust archive

Reverse dependencies:

Reverse imports:	DIDHAD, rdlearn
Reverse suggests:	tidyhte

Linking:

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