Skip to main content
. 2022 May 14;22(10):3737. doi: 10.3390/s22103737
Algorithm 1 Pseudocode for Outlier Removal
The data to evaluate are imported.
Statistical parameters (Mean, Covariance) are calculated.
Calculation of the parameters (New_Data, inverse covariance) to obtain the Mahalanobis distance.
  • -

    Calculation of New_Data = data minus the mean.

  • -

    Inverse covariance is calculated.

Product of New_Data and inverse covariance.
Critical value is obtained according to a chi-square distribution with the function ncx2inv with MATLAB.
Data are separated according to the critical value.
Outliers are removed and maintained matrices are created.