# Simple Local Polynomial Density Estimators

arXiv: https://arxiv.org/abs/1811.11512 · HTML: https://mlsanity.com/paper/1811.11512/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Nov 2018.

## Built on by (most cited first, 5 of 5)

- [A Causal Framework for Evaluating Deferring Systems](https://mlsanity.com/paper/2405.18902/) (2024)
- [Boosting in Univariate Nonparametric Maximum Likelihood Estimation](https://mlsanity.com/paper/2101.08505/) (2021)
- [Bayes Risk Consistency of Nonparametric Classification Rules for Spike Trains Data](https://mlsanity.com/paper/2308.04796/) (2023)
- [Compactly supported radial basis functions as probability density functions](https://mlsanity.com/paper/2607.26759/) (2026)
- [Local polynomial density ratio estimation](https://mlsanity.com/paper/2609.38412/) (2026)

## Abstract (arXiv)

This paper introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automatic, but does not require pre-binning or any other transformation of the data. We study the main asymptotic properties of the estimator, and use these results to provide principled estimation, inference, and bandwidth selection methods. As a substantive application of our results, we develop a novel discontinuity in density testing procedure, an important problem in regression discontinuity designs and other program evaluation settings. An illustrative empirical application is given. Two companion Stata and R software packages are provided.