A multitest procedure for testing MTP2 for Gaussian distributions

Konrad Furmańczyk

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 24, 8865-8874

Abstract: We present a new test for MTP2 for Gaussian distributions. Our test is based on multiple testing whether all coefficients are non-positive beyond the diagonal of the inverse covariance matrix. In the low dimensional case, we use test statistics based on the inverse empirical covariance matrix and for the high dimensional case, we apply correction of the glasso estimator (desparsified glasso estimator, van de Geer et al. (2014)). In a simulation study, we compare our test with the universal test (Wasserman, Ramdas, and Balakrishnan (2020)) and we check the power and control of the type I error of these tests.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2022.2081339 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:52:y:2023:i:24:p:8865-8874

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2022.2081339

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().