Publication

lpcde: Estimation and Inference for Local Polynomial Conditional Density Estimators

Rajita Ramesh Chandak
2025

Abstract

Conditional cumulative distribution functions (CDFs), conditional probability density functions (PDFs), and derivatives thereof, are important parameters of interest in statistics, econometrics, and other data science disciplines. The package lpcde implements new estimation and inference methods for conditional CDFs, conditional PDFs, and derivatives thereof, employing the kernelbased local polynomial smoothing approach introduced in Cattaneo et al. (2024a).

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lpcde: Estimation and Inference for Local Polynomial Conditional Density Estimators

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