Local Polynomial Density Methods

The lpdensity package implements bandwidth selection, point estimation, inference and graphical procedures for local polynomial distribution and density methods.

• lpdensity: local polynomial distribution and density estimation with robust bias-corrected pointwise and uniform inference.
• lpbwdensity: data-driven bandwidth selection for local polynomial distribution and density estimation.

Python Implementation

To install/update in Python type:

pip install lpdensity

• Help: PyPI repository.

• Replication: py-script.

R Implementation

To install/update in R type:

install.packages('lpdensity')

• Help: R Manual, CRAN repository.

• Replication: R-script.

Stata Implementation

To install/update in Stata type:

net install lpdensity, from(https://raw.githubusercontent.com/nppackages/lpdensity/main/stata) replace

• Help: lpdensity, lpbwdensity.

• Replication: do-file.

References

Software and Implementation

• Cattaneo, Jansson and Ma (2022): lpdensity: Local Polynomial Density Estimation and Inference.
  Journal of Statistical Software 101(2): 1-25.

Technical and Methodological

• Cattaneo, Jansson and Ma (2020): Simple Local Polynomial Density Estimators.
  Journal of the American Statistical Association 115(531): 1449-1455.
  Supplemental appendix.

• Cattaneo, Jansson and Ma (2024): Local Regression Distribution Estimators.
  Journal of Econometrics 240(2): 105074.
  Supplemental Appendix.

Funding

This work was supported in part by the National Science Foundation through grants SES-1459931, SES-1459967, SES-1947805, and SES-1947662.