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nprobust: Nonparametric Robust Estimation and Inference Methods usingLocal Polynomial Regression and Kernel Density Estimation

Tools for data-driven statistical analysis using local polynomial regression and kernel density estimation methods as described in Calonico, Cattaneo and Farrell (2018, <doi:10.1080/01621459.2017.1285776>): '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 of this package are described in Calonico, Cattaneo and Farrell (2019, <doi:10.18637/jss.v091.i08>).

Version:0.5.0
Depends:R (≥ 3.1.1)
Imports:Rcpp,ggplot2
LinkingTo:Rcpp,RcppArmadillo
Published:2025-04-14
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>
License:GPL-2
NeedsCompilation:yes
Citation:nprobust citation info
CRAN checks:nprobust results

Documentation:

Reference manual:nprobust.html ,nprobust.pdf

Downloads:

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

Reverse dependencies:

Reverse imports:DIDHAD,rdlearn
Reverse suggests:tidyhte

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=nprobustto link to this page.


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