Regression with Variable Dimension Covariates
Statistics Theory
2023-09-26 v1 Methodology
Statistics Theory
Abstract
Regression is one of the most fundamental statistical inference problems. A broad definition of regression problems is as estimation of the distribution of an outcome using a family of probability models indexed by covariates. Despite the ubiquitous nature of regression problems and the abundance of related methods and results there is a surprising gap in the literature. There are no well established methods for regression with a varying dimension covariate vectors, despite the common occurrence of such problems. In this paper we review some recent related papers proposing varying dimension regression by way of random partitions.
Cite
@article{arxiv.2309.14120,
title = {Regression with Variable Dimension Covariates},
author = {Peter Mueller and Fernando Andrés Quintana and Garritt L. Page},
journal= {arXiv preprint arXiv:2309.14120},
year = {2023}
}