Package: nprobust
Type: Package
Title: Nonparametric Robust Estimation and Inference Methods using
        Local Polynomial Regression and Kernel Density Estimation
Version: 0.2.1
Date: 2019-10-29
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: 2019-10-30 14:49:16 UTC; nsc2136
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2019-10-30 15:20:03 UTC
