On Variable Screening in Multiple Nonparametric Regression Model
Methodology
2021-01-19 v3 Statistics Theory
Statistics Theory
Abstract
In this article, we study the problem of variable screening in multiple nonparametric regression model. The proposed methodology is based on the fact that the partial derivative of the regression function with respect to the irrelevant variable should be negligible. The Statistical property of the proposed methodology is investigated under both cases : (i) when the variance of the error term is known, and (ii) when the variance of the error term is unknown. Moreover, we establish the practicality of our proposed methodology for various simulated and real data related to interdisciplinary sciences such as Economics, Finance and other sciences.
Keywords
Cite
@article{arxiv.1909.10739,
title = {On Variable Screening in Multiple Nonparametric Regression Model},
author = {Subhra Sankar Dhar and Prashant Jha and Aranyak Acharyya},
journal= {arXiv preprint arXiv:1909.10739},
year = {2021}
}
Comments
There were several modifications needed in Sections 3, 4, and Appendix, due to errors