nprobust
R package 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>).
Keywords for this software
References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
Sorted by year (- Matias D. Cattaneo, Michael Jansson, Xinwei Ma: lpdensity: Local Polynomial Density Estimation and Inference (2022) not zbMATH
- Sebastian Calonico; Matias Cattaneo; Max Farrell: nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference (2019) not zbMATH
- Calonico, Sebastian; Cattaneo, Matias D.; Titiunik, Rocio: Robust nonparametric confidence intervals for regression-discontinuity designs (2014)