dc.contributor.author | Sipilä, Mika | |
dc.contributor.author | Muehlmann, Christoph | |
dc.contributor.author | Nordhausen, Klaus | |
dc.contributor.author | Taskinen, Sara | |
dc.date.accessioned | 2023-12-20T10:18:07Z | |
dc.date.available | 2023-12-20T10:18:07Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Sipilä, M., Muehlmann, C., Nordhausen, K., & Taskinen, S. (2024). Robust second-order stationary spatial blind source separation using generalized sign matrices. <i>Spatial Statistics</i>, <i>59</i>, Article 100803. <a href="https://doi.org/10.1016/j.spasta.2023.100803" target="_blank">https://doi.org/10.1016/j.spasta.2023.100803</a> | |
dc.identifier.other | CONVID_197360950 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/92425 | |
dc.description.abstract | Consider a spatial blind source separation model in which the observed multivariate spatial data are assumed to be a linear mixture of latent stationary spatially uncorrelated random fields. The objective is to recover an unknown mixing procedure as well as the latent random fields. Recently, spatial blind source separation methods that are based on the simultaneous diagonalization of two or more scatter matrices were proposed. In cases involving uncontaminated data, such methods can solve the blind source separation problem, however, in the presence of outlying observations, these methods perform poorly. We propose a robust blind source separation method that employs robust global and local covariance matrices based on generalized spatial signs in simultaneous diagonalization. Simulation studies are employed to illustrate the robustness and efficiency of the proposed methods in various scenarios. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Elsevier | |
dc.relation.ispartofseries | Spatial Statistics | |
dc.rights | CC BY 4.0 | |
dc.subject.other | affine equivariance | |
dc.subject.other | bias | |
dc.subject.other | multivariate spatial data | |
dc.subject.other | scatter matrix | |
dc.subject.other | spatial signs | |
dc.title | Robust second-order stationary spatial blind source separation using generalized sign matrices | |
dc.type | article | |
dc.identifier.urn | URN:NBN:fi:jyu-202312208419 | |
dc.contributor.laitos | Matematiikan ja tilastotieteen laitos | fi |
dc.contributor.laitos | Department of Mathematics and Statistics | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.relation.issn | 2211-6753 | |
dc.relation.volume | 59 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © 2023 The Author(s). Published by Elsevier B.V. | |
dc.rights.accesslevel | openAccess | fi |
dc.subject.yso | paikkatietoanalyysi | |
dc.subject.yso | signaalinkäsittely | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p28516 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p12266 | |
dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
dc.relation.doi | 10.1016/j.spasta.2023.100803 | |
jyx.fundinginformation | The work of CM and KN was supported by the Austrian Science Fund P31881-N32. The work of KN and ST was supported by the COST Action HiTEc (CA21163). The work of MS was supported by the Vilho, Yrjö and Kalle Väisälä Fund, Finland. | |
dc.type.okm | A1 | |