Doubly-nonparametric generalized additive models
Methodology
2017-09-18 v2
Abstract
The popular generalized additive model framework is extended to allow both the mean curves and the response distribution to be nonparametric. The approach is demonstrated to be a flexible yet parsimonious tool for data analysis in its own right, as well as being a useful tool for model selection and diagnosis in the classical generalized additive model framework. Finite-sample performance of the method is examined via various simulation settings and the method is illustrated on two data analysis examples.
Keywords
Cite
@article{arxiv.1603.00921,
title = {Doubly-nonparametric generalized additive models},
author = {Alan Huang and Nanxi Zhang},
journal= {arXiv preprint arXiv:1603.00921},
year = {2017}
}
Comments
15 pages double-spaced, 3 figures