Network constrained covariate coefficient and connection sign estimation

Matthias Weber, Jonas Striaukas (), Martin Schumacher and Harald Binder
Additional contact information
Jonas Striaukas: Universite catholique de Louvain, CORE
Martin Schumacher: Institute of Medical Biometry and Statistics, University of Freiburg
Harald Binder: Institute of Medical Biometry and Statistics, University of Freiburg

No 8, Bank of Lithuania Discussion Paper Series from Bank of Lithuania

Abstract: Often, variables are linked to each other via a network. When such a network structure is known, this knowledge can be incorporated into regularized regression settings. In particular, an additional network penalty can be added on top of another penalty term, such as a Lasso penalty. However, when the type of interaction via the network is unknown (that is, whether connections are of an activating or a repressing type), the connection signs have to be estimated simultaneously with the covariate coefficients. This can be done with an algorithm iterating a connection sign estimation step and a covariate coefficient estimation step. We show detailed simulation results of such an algorithm. The algorithm performs well in a variety of settings. We also briefly describe the R-package that we developed for this purpose, which is publicly available.

Keywords: network regression; network penalty; connection sign estimation; regularized regression (search for similar items in EconPapers)
Pages: 23 pages
Date: 2018-06-20
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.lb.lt/en/publications/no-8-matthias-we ... tion-sign-estimation Full text (application/pdf)
Our link check indicates that this URL is bad, the error code is: 403 Forbidden

Related works:
Working Paper: Network-Constrained Covariate Coefficient and Connection Sign Estimation (2020)
Working Paper: Network constrained covariate coefficient and connection sign estimation (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:lie:dpaper:8

Access Statistics for this paper

More papers in Bank of Lithuania Discussion Paper Series from Bank of Lithuania Bank of Lithuania Gedimino pr. 6, LT-01103 Vilnius, Lithuania. Contact information at EDIRC.
Bibliographic data for series maintained by Aurelija Proskute ().