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nprobust 0.1.4

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

Released Jan 10, 2019 by Sebastian Calonico

This package cannot yet be used with Renjin it depends on other packages which are not available: ggplot2 3.1.0 An older version of this package is more compatible with Renjin.

Dependencies

ggplot2 3.1.0 RcppArmadillo 0.9.200.5.0 Rcpp

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 and kdrobust() for kernel density point estimation and robust bias-corrected inference. Several optimal bandwidth selection procedures are computed by lpbwselect() and kdbwselect() for local polynomial and kernel density estimation, respectively. Finally, nprobust.plot() for density and regression plots with robust confidence interval.

Source

R
C++

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