Package: nprobust
Type: Package
Title: Nonparametric Robust Estimation and Inference Methods using
        Local Polynomial Regression and Kernel Density Estimation
Version: 0.5.0
Date: 2025-04-12
Authors@R: c(person(given = c("Sebastian"),
                      family = "Calonico",
                      role = c("aut", "cre"),
                      email = "scalonico@ucdavis.edu"),
               person(given = c("Matias", "D."),
                      family = "Cattaneo",
                      role = "aut",
                      email = "cattaneo@princeton.edu"),
               person(given = c("Max", "H."),
                      family = "Farrell",
                      role = "aut",
                      email = "maxhfarrell@ucsb.edu"))
Description: 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>).
Depends: R (>= 3.1.1)
License: GPL-2
Imports: Rcpp, ggplot2
LinkingTo: Rcpp, RcppArmadillo
Packaged: 2025-04-13 13:03:38 UTC; dell5
NeedsCompilation: yes
Author: Sebastian Calonico [aut, cre],
  Matias D. Cattaneo [aut],
  Max H. Farrell [aut]
Maintainer: Sebastian Calonico <scalonico@ucdavis.edu>
Repository: CRAN
Date/Publication: 2025-04-14 07:50:06 UTC
Built: R 4.3.3; x86_64-apple-darwin20; 2025-04-14 08:51:25 UTC; unix
Archs: nprobust.so.dSYM
