The Review of Economics and Statistics Vol. 89 No. 4 2007
Nonparametric Estimation of Regression Functions in the Presence of Irrelevant Regressors
Abstract
In this paper we consider a nonparametric regression model that admits a mix of continuous and discrete regressors, some of which may in fact be redundant (that is, irrelevant). We show that, asymptotically, a data-driven least squares cross-validation method can remove irrelevant regressors. Simulations reveal that this “automatic dimensionality reduction” feature is very effective in finite-sample settings.
- DOI
- 10.1162/rest.89.4.784
- Volume
- 89
- Issue
- 4
- Pages
- 784-789
- Language
- en
- Sources
- openalex crossref