Package: nprobust
Type: Package
Title: Nonparametric Robust Estimation and Inference Methods using
        Local Polynomial Regression and Kernel Density Estimation
Version: 0.3.0
Date: 2020-03-24
Author: Sebastian Calonico <sebastian.calonico@columbia.edu>, Matias D. Cattaneo <cattaneo@princeton.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>
Maintainer: Sebastian Calonico <sebastian.calonico@columbia.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: 2020-03-31 20:52:14 UTC; SCalonico
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2020-04-02 05:10:03 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 13:02:05 UTC; windows
Archs: i386, x64
