6533b856fe1ef96bd12b3062
RESEARCH PRODUCT
Test of the Latent Dimension of a Spatial Blind Source Separation Model
Christoph MuehlmannFrancois BachocKlaus NordhausenMengxi Yisubject
Statistics and Probabilitymonimuuttujamenetelmätsignaalinkäsittelykernel functionFOS: Mathematicsspatial bootstrapMathematics - Statistics Theorymultivariate spatial dataStatistics Theory (math.ST)paikkatietoanalyysiStatistics Probability and Uncertaintyasymptotic distributionsignal numberdescription
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. peerReviewed
year | journal | country | edition | language |
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2024-01-01 |