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nprobust
View on CRAN: Click
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Download and install nprobust package within the R console
Install from CRAN:
install.packages("nprobust")
Install from Github:
library("remotes")
install_github("cran/nprobust")
Install by package version:
library("remotes")
install_version("nprobust", "0.4.0")
Attach the package and use:
library("nprobust")
Maintained by
Sebastian Calonico
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-11-07
Latest Update: 2020-08-26
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, ).
How to cite:
Sebastian Calonico (2016). nprobust: Nonparametric Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density Estimation. R package version 0.4.0, https://cran.r-project.org/web/packages/nprobust
Previous versions and publish date:
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Functions, R codes and Examples using
the nprobust R package
Some associated functions: kdbwselect . kdrobust . lpbwselect . lprobust . nprobust-package . nprobust.plot .
Some associated R codes: RcppExports.R . kdbwselect.R . kdrobust.R . lpbwselect.R . lprobust.R . npfunctions.R . nprobust.plot.R . Full nprobust package functions and examples
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