Exploring Hoover and Perez's experimental designs using global sensitivity analysis
Computation
2014-01-23 v1
Abstract
This paper investigates variable-selection procedures in regression that make use of global sensitivity analysis. The approach is combined with existing algorithms and it is applied to the time series regression designs proposed by Hoover and Perez. A comparison of an algorithm employing global sensitivity analysis and the (optimized) algorithm of Hoover and Perez shows that the former significantly improves the recovery rates of original specifications.
Keywords
Cite
@article{arxiv.1401.5617,
title = {Exploring Hoover and Perez's experimental designs using global sensitivity analysis},
author = {William Becker and Paolo Paruolo and Andrea Saltelli},
journal= {arXiv preprint arXiv:1401.5617},
year = {2014}
}
Comments
27 pages, 2 figures