The paper contains a nice literature overview.
Reference
Thomas Nagler “A generic approach to nonparametric function estimation with mixed data” (2018) // Statistics & Probability Letters. Publisher: Elsevier BV. Vol. 137. Pp. 326–330. DOI: 10.1016/j.spl.2018.02.040
Abstract
Most nonparametric function estimators can only handle continuous data. We show that making discrete variables continuous by adding noise is justified under suitable conditions on the noise distribution. This principle is widely applicable, including density and regression function estimation.
Bib
@Article{nagler2018,
title = {A generic approach to nonparametric function estimation with mixed data},
abstract = {Most nonparametric function estimators can only handle continuous data. We show that making discrete variables continuous by adding noise is justified under suitable conditions on the noise distribution. This principle is widely applicable, including density and regression function estimation.},
volume = {137},
issn = {0167-7152},
doi = {10.1016/j.spl.2018.02.040},
arxiv = {1704.07457},
journal = {Statistics \& Probability Letters},
publisher = {Elsevier BV},
author = {Nagler, Thomas},
year = {2018},
month = {jun},
pages = {326–330}
}