Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions
Year: 2012
Type: article
Abstract: We propose a data-driven least-square cross-validation method to optimally select smoothing parameters for the nonparametric estimation of conditional cumulative distribution functions and conditional quantile functions. We allow for general multivariate covariates that can be continuous, categorical, or a mix of either. We provide asymptotic analysis, examine finite-sample properties via Monte Carlo simulation, and consider an application involving testing for first-order stochastic dominance of children’s health conditional on parental education and income. This article has supplementary materials online.
Authors: Qi Li, Juan Lin, Jeffrey S. Racine
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Award: G3157016747
OpenAlex ID: W2011416863