A note on the Lasso for Gaussian graphical model selection
Nicolai Meinshausen
Statistics & Probability Letters, 2008, vol. 78, issue 7, 880-884
Abstract:
Inspired by the success of the Lasso for regression analysis, it seems attractive to estimate the graph of a multivariate normal distribution by l1-norm penalized likelihood maximization. We examine some properties of the estimator and show that care has to be taken with interpretation of results as the estimator is not consistent for some graphs.
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(07)00294-5
Full text for ScienceDirect subscribers only
Related works:
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:eee:stapro:v:78:y:2008:i:7:p:880-884
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().