Consistency and asymptotic normality of M-estimates of scatter on Grassmann manifolds

Corina Ciobotaru and Christian Mazza

Journal of Multivariate Analysis, 2022, vol. 190, issue C

Abstract: This work proposes a study of M-estimates of scatter for matrix angular central Gaussian distributions on Grassmann manifold G(m,r) of all vector subspaces of dimension r of Rm. Such distributions are associated to random subspaces generated by r i.i.d. multivariate centred normal random vectors, and are of interest in Bayesian model selection for cointegration. We provide a careful study of the existence and the unicity of such M-estimators using geometrical arguments, and then study their consistency and asymptotic normality.

Keywords: Covariance matrix; Grassmann manifold; Matrix central angular distribution (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X2200032X
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:jmvana:v:190:y:2022:i:c:s0047259x2200032x

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

DOI: 10.1016/j.jmva.2022.104998

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().