Implements local polynomial point estimation with robust bias-corrected uniform confidence intervals.
Project description
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 (cattaneo@princeton.edu)
Xinwei Ma (x1ma@ucsd.edu)
Michael Jansson (mjansson@econ.berkeley.edu)
Rajita Chandak (maintainer) (rchandak@princeton.edu)
Website
https://nppackages.github.io/lpdensity/
Installation
To install/update use pip
pip install lpdensity
Usage
from lpdensity import lpdensity, lpbwdensity
Dependencies
- numpy
- pandas
- math
- scipy
- plotnine
References
For overviews and introductions, see lpdensity website
Software Implementation
-Cattaneo, Jansson and Ma (2021): lpdensity: Local Polynomial Density Estimation and Inference..
Journal of Statistical Software, forthcoming.
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 (2021): Local Regression Distribution Estimators.
Journal of Econometrics, forthcoming.
Supplemental Appendix.
Project details
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