Order Determination in Second-Order Source Separation Models Using Data Augmentation
Year of publication
2024
Authors
Radojičić, Una; Nordhausen, Klaus
Abstract
We propose a robust estimator for the number of latent components in an internal noise model within the second-order source separation (SOS) framework. Our approach utilizes a data augmentation strategy in conjunction with the robust SOS approach eSAM-AMUSE, which combines information from eigenvalues and variations of eigenvectors of eSAM-AMUSE. The resulting dimension estimate can be visualized using a ladle plot. Through a simulation study, we demonstrate the superior properties of the new estimator, which outperforms the bootstrap-based AMUSEladle estimator.
Show moreOrganizations and authors
University of Jyväskylä
Nordhausen Klaus 
Publication type
Publication format
Article
Parent publication type
Conference
Article type
Other article
Audience
ScientificPeer-reviewed
Peer-ReviewedMINEDU's publication type classification code
A4 Article in conference proceedingsPublication channel information
Parent publication name
Combining, Modelling and Analyzing Imprecision, Randomness and Dependence
Publisher
Pages
371-379
ISSN
ISBN
Publication forum
Publication forum level
1
Open access
Open access in the publisher’s service
No
Self-archived
Yes
Other information
Fields of science
Statistics and probability
Keywords
[object Object],[object Object]
Publication country
Switzerland
Internationality of the publisher
International
Language
English
International co-publication
Yes
Co-publication with a company
No
DOI
10.1007/978-3-031-65993-5_46
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes