Exploring the changes in a series of measurements - The comparison of the two-dimensional correlation analysis and the alteration analysis

- Alteration analysis (ALA) was introduced to expand the possibilities of 2D correlation.
- This simple approach allows to work in 2D analysis efficiently.
- 2DCOR and ALA have two different approaches to the same problem.
- ALA shows more details on the individual changes.
- ALA is not only an extension of 2DCOR in 3D analysis, but a great alternative in 2D as well.

Alteration analysis (ALA) has been recently introduced to expand the two-dimensional correlation analysis (2DCOR) into further dimensions. 2DCOR is unable to work with 3D data arrays composed from a series of 2D measurements, but ALA has the advantage that it does not increase (multiply) the dimensions of the original data sets. Thus, it can easily be applied to more complex systems. ALA, however, does not work only with 3D arrays, but with matrices as well. In this study we present a comparison of the two methods. ALA has a different mathematical background, indicating that it has different properties. Therefore, some drawbacks are inevitable, however, ALA has a number of advantages over 2DCOR. While 2DCOR emphasises the correlation between the changes, ALA focuses on individual changes and provides more detailed information about them. Furthermore, we demonstrate that the connection between these changes can also be described with ALA. Besides, ALA simplifies the visual representation, because instead of two 2D maps (2DCOR) the information is shown on a single linear graph. Therefore, ALA is not only an extension, but it can be an alternative to 2DCOR.