dc.contributor.author | Muehlmann, Christoph | |
dc.contributor.author | Bachoc, Francois | |
dc.contributor.author | Nordhausen, Klaus | |
dc.contributor.author | Yi, Mengxi | |
dc.date.accessioned | 2023-02-09T12:33:51Z | |
dc.date.available | 2023-02-09T12:33:51Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Muehlmann, C., Bachoc, F., Nordhausen, K., & Yi, M. (2024). Test of the Latent Dimension of a Spatial Blind Source Separation Model. <i>Statistica Sinica</i>, <i>34</i>(2), Early online. <a href="https://doi.org/10.5705/ss.202021.0326" target="_blank">https://doi.org/10.5705/ss.202021.0326</a> | |
dc.identifier.other | CONVID_160509449 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/85425 | |
dc.description.abstract | We assume a spatial blind source separation model in which the observed multivariate spatial data is a linear mixture of latent spatially uncorrelated random fields containing a number of pure white noise components. We propose a test on the number of white noise components and obtain the asymptotic distribution of its statistic for a general domain. We also demonstrate how computations can be facilitated in the case of gridded observation locations. Based on this test, we obtain a consistent estimator of the true dimension. Simulation studies and an environmental application in the Supplemental Material demonstrate that our test is at least comparable to and often outperforms bootstrap-based techniques, which are also introduced in this paper. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Institute of Statistical Science, Academia Sinica | |
dc.relation.ispartofseries | Statistica Sinica | |
dc.rights | In Copyright | |
dc.subject.other | asymptotic distribution | |
dc.subject.other | kernel function | |
dc.subject.other | multivariate spatial data | |
dc.subject.other | signal number | |
dc.subject.other | spatial bootstrap | |
dc.title | Test of the Latent Dimension of a Spatial Blind Source Separation Model | |
dc.type | article | |
dc.identifier.urn | URN:NBN:fi:jyu-202302091703 | |
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.format.pagerange | Early online | |
dc.relation.issn | 1017-0405 | |
dc.relation.numberinseries | 2 | |
dc.relation.volume | 34 | |
dc.type.version | acceptedVersion | |
dc.rights.copyright | © Institute of Statistical Science, Academia Sinica | |
dc.rights.accesslevel | openAccess | fi |
dc.subject.yso | monimuuttujamenetelmät | |
dc.subject.yso | paikkatietoanalyysi | |
dc.subject.yso | signaalinkäsittely | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2131 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p28516 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p12266 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.5705/ss.202021.0326 | |
jyx.fundinginformation | The work of Christoph Muehlmann, Klaus Nordhausen and Mengxi Yi are supported by the Austrian Science Fund (No. P31881-N32). The work of Mengxi Yi is also supported by the National Natural Science Foundation of China (No. 12101119). | |
dc.type.okm | A1 | |