lpdensity 2.4.3

Implements local polynomial point estimation with robust bias-corrected uniform confidence intervals.

LPDENSITY

The lpdensity package provides Stata and R implementations of bandwidth selection, point estimation and inference procedures for local polynomial distribution and density methods.

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

Authors

Matias D. Cattaneo ([e-mail])

Xinwei Ma ([e-mail])

Michael Jansson ([e-mail])

Rajita Chandak (maintainer) ([e-mail])

Website

https://nppackages.github.io/lpdensity/

Manual

https://github.com/nppackages/lpdensity/tree/master/Python/lpdensity/docs/build/latex/lpdensity.pdf

Installation

To install/update use pip

pip install lpdensity

Usage

from lpdensity import lpdensity, lpbwdensity

Dependencies

• numpy
• pandas
• math
• scipy
• sympy
• plotnine

References

For overviews and introductions, see lpdensity website

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

• Cattaneo, M. D., M. Jansson, and X. Ma (2023). Local Regression Distribution Estimators.
  Journal of Econometrics, forthcoming.
  Supplemental Appendix.

• Calonico, S., M. D. Cattaneo, and M. H. Farrell (2018): On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference.
  Journal of the American Statistical Association 113(522): 767-779.

• Calonico, S., M. D. Cattaneo, and M. H. Farrell (2022): Coverage Error Optimal Confidence Intervals for Local Polynomial Regression.
  Bernoulli 28(4): 2998-3022.

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