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nprobust (version 0.4.0)

Nonparametric Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density Estimation

Description

Tools for data-driven statistical analysis using local polynomial regression and kernel density estimation methods as described in Calonico, Cattaneo and Farrell (2018, ): 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, ).

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Install

install.packages('nprobust')

Monthly Downloads

400

Version

0.4.0

License

GPL-2

Last Published

August 26th, 2020

Functions in nprobust (0.4.0)

kdrobust

Kernel Density Methods with Robust Bias-Corrected Inference
nprobust.plot

Graphical Presentation of Results from nprobust Package.
lpbwselect

Bandwidth Selection Procedures for Local Polynomial Regression Estimation and Inference
lprobust

Local Polynomial Methods with Robust Bias-Corrected Inference
nprobust-package

Nonparametric Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density Estimation
kdbwselect

Bandwidth Selection Procedures for Kernel Density Estimation and Inference