Robust Coefficients of Correlation or Spatial Autocorrelation Based on Implicit Weighting

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F22%3A00560805" target="_blank" >RIV/67985807:_____/22:00560805 - isvavai.cz</a>
Result on the web
<a href="https://dx.doi.org/10.1007/s42952-022-00184-2" target="_blank" >https://dx.doi.org/10.1007/s42952-022-00184-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s42952-022-00184-2" target="_blank" >10.1007/s42952-022-00184-2</a>

Result language
angličtina
Original language name
Robust Coefficients of Correlation or Spatial Autocorrelation Based on Implicit Weighting
Original language description
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.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GA22-02067S" target="_blank" >GA22-02067S: AppNeCo: Approximate Neurocomputing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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