Download PDFOpen PDF in browserPrincipal Component Analysis of Multivariate Spatial Functional DataEasyChair Preprint 1432418 pages•Date: August 7, 2024AbstractThis paper is dedicated to dimension reduction techniques for multivariate spatially indexed functional data. We introduce an innovative method named Spatial Multivariate Funtional Principal Component Analysis (SMFPCA), which stands for principal component analysis for multivariate spatial functional data. Unlike the conventional Multivariate Karhunen-Loève approach, SMFPCA excels at effectively capturing spatial dependencies among multiples functions. Keyphrases: Functional Principal Component Analysis, Spatial-functional Principal Component Analysis, functional data analysis, multivariate analysis, spectral analysis
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