Robust Coefficients of Correlation or Spatial Autocorrelation Based on Implicit Weighting

0560805 - ÚI 2023 RIV KR eng J - Journal Article
Kalina, Jan
Robust Coefficients of Correlation or Spatial Autocorrelation Based on Implicit Weighting.
Journal of the Korean Statistical Society. Roč. 51, č. 4 (2022), s. 1247-1267. ISSN 1226-3192. E-ISSN 2005-2863
R&D Projects: GA ČR(CZ) GA22-02067S
Institutional support: RVO:67985807
Keywords : Weighting Robustness * Breakdown point * Moran coefficient * Image analysis * Template matching
OECD category: Statistics and probability
Impact factor: 0.6, year: 2022
Method of publishing: Limited access
https://dx.doi.org/10.1007/s42952-022-00184-2

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.
Permanent Link: https://hdl.handle.net/11104/0333587