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 <sebastian.calonico@columbia.edu>, Matias D. Cattaneo <cattaneo@princeton.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>
MaintainerSebastian Calonico <sebastian.calonico@columbia.edu>
LicenseGPL-2
Version0.4.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("nprobust")

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nprobust documentation built on Aug. 26, 2020, 5:12 p.m.