Algorithms and Complexity for Variants of Covariates Fine Balance
Data Structures and Algorithms
2020-09-18 v1 Discrete Mathematics
Combinatorics
Optimization and Control
Statistics Theory
Statistics Theory
Abstract
We study here several variants of the covariates fine balance problem where we generalize some of these problems and introduce a number of others. We present here a comprehensive complexity study of the covariates problems providing polynomial time algorithms, or a proof of NP-hardness. The polynomial time algorithms described are mostly combinatorial and rely on network flow techniques. In addition we present several fixed-parameter tractable results for problems where the number of covariates and the number of levels of each covariate are seen as a parameter.
Keywords
Cite
@article{arxiv.2009.08172,
title = {Algorithms and Complexity for Variants of Covariates Fine Balance},
author = {Dorit S. Hochbaum and Asaf Levin and Xu Rao},
journal= {arXiv preprint arXiv:2009.08172},
year = {2020}
}