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Robust Coefficients of Correlation or Spatial Autocorrelation Based on Implicit Weighting
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SYSNO ASEP 0560805 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Robust Coefficients of Correlation or Spatial Autocorrelation Based on Implicit Weighting Author(s) Kalina, Jan (UIVT-O) RID, SAI, ORCID Source Title Journal of the Korean Statistical Society. - : Elsevier - ISSN 1226-3192
Roč. 51, č. 4 (2022), s. 1247-1267Number of pages 21 s. Language eng - English Country KR - Korea, Republic of Keywords Weighting Robustness ; Breakdown point ; Moran coefficient ; Image analysis ; Template matching OECD category Statistics and probability R&D Projects GA22-02067S GA ČR - Czech Science Foundation (CSF) Method of publishing Limited access Institutional support UIVT-O - RVO:67985807 UT WOS 000844582800001 EID SCOPUS 85137029438 DOI 10.1007/s42952-022-00184-2 Annotation Pearson product-moment correlation coefficient represents a fundamental tool for measuring linear association between two data vectors. In various applications, it is often reasonable to consider its weighted version known as the weighted correlation coefficient. This paper starts with theoretical considerations related to properties of the weighted correlation coefficient, particularly to its local robustness and relationship to other similarity measures. Inspired by the least weighted squares regression estimator, a robust correlation coefficient is investigated here together with its spatial autocorrelation extension. Finally, the considered methods are investigated in two image processing tasks. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2023 Electronic address https://dx.doi.org/10.1007/s42952-022-00184-2
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