nprobust: Nonparametric Robust Estimation and Inference Methods using Local 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>).

Package details

AuthorSebastian Calonico [aut, cre], Matias D. Cattaneo [aut], Max H. Farrell [aut]
MaintainerSebastian Calonico <scalonico@ucdavis.edu>
LicenseGPL-2
Version0.5.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("nprobust")

Try the nprobust package in your browser

Any scripts or data that you put into this service are public.

nprobust documentation built on April 14, 2025, 9:07 a.m.