Uncertainty ranking: Pearson’s correlation¶
This method deals with analyzing the influence the random vector has on a random variable which is being studied for uncertainty. Here we attempt to measure linear relationships that exist between and the different components .
Pearson’s correlation coefficient , defined in , measures the strength of a linear relation between two random variables and . If we have a sample made up of pairs , , …, , we can obtain an estimation of Pearson’s coefficient. The hierarchical ordering of Pearson’s coefficients is of interest in the case where the relationship between and variables is close to being a linear relation:
To obtain an indication of the role played by each in the dispersion of , the idea is to estimate Pearson’s correlation coefficient for each . One can then order the variables taking absolute values of the correlation coefficients: the higher the value of the greater the impact the variable has on the dispersion of .
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