The nprobust package provides R and Stata implementations of bandwidth selection, point estimation and inference procedures for nonparametric kernel-based density and local polynomial methods.
This work was supported by the National Science Foundation through grant SES-1459931 and SES-1947805.
https://nppackages.github.io/nprobust
Please email: [email protected]
To install/update in R type:
install.packages('nprobust')
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Help: R Manual, CRAN repository.
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Replication: R-script, nprobust_data.
To install/update in Stata type:
net install nprobust, from(https://raw.githubusercontent.com/nppackages/nprobust/master/stata) replace
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Help: kdrobust, kdbwselect, lprobust, lpbwselect.
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Replication: do-file, nprobust_data.
- Calonico, Cattaneo and Farrell (2019): nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference.
Journal of Statistical Software 91(8): 1-33.
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Calonico, Cattaneo and Farrell (2018): On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference.
Journal of the American Statistical Association 113(522): 767-779.
Supplemental Appendix. -
Calonico, Cattaneo and Farrell (2022): Coverage Error Optimal Confidence Intervals for Local Polynomial Regression.
Bernoulli 28(4): 2998-3022.
Supplemental Appendix.