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).
- Version0.4.0
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- nprobust citation info
- Last release08/26/2020
Team
Sebastian Calonico
Matias D. Cattaneo
Show author detailsRolesAuthorMax H. Farrell
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