Large Datasets, Bias and Model Oriented Optimal Design of Experiments
Methodology
2018-12-03 v1 Applications
Abstract
We review recent literature that proposes to adapt ideas from classical model based optimal design of experiments to problems of data selection of large datasets. Special attention is given to bias reduction and to protection against confounders. Some new results are presented. Theoretical and computational comparisons are made.
Cite
@article{arxiv.1811.12682,
title = {Large Datasets, Bias and Model Oriented Optimal Design of Experiments},
author = {Elena Pesce and Eva Riccomagno},
journal= {arXiv preprint arXiv:1811.12682},
year = {2018}
}