Adam WALANUS & Dorota NALEPKA
A difficulty in correlating many profiles, where none is the main or reference one, lies in a fact that the number of possible correlations grows exponentially with the number of profiles. Application of a Monte Carlo method makes it very probable to discover the best correlations in a reasonable amount of computing time. The quality of a correlation is measured by a metric of dissimilarity of the samples. The final result, given in graphical form, is comprised of lines connecting samples from different profiles. The number of lines (correlations across profiles) is user-defined and can vary from one to dozens. The number of profiles, samples, and variables depends only on the computational resources. Large problems need longer computation times to achieve stable results.
The full text (pdf) from Annales Societatis Geologorum Poloniae (2006), vol. 76: 215–224.
Download the program MultCorr.exe.
Example of data file (one profile). Each profile for correlation is stored in txt file with values separated by tabulator.
Text data file in MS Excel.
Program creates high resolution bitmaps ready for printing.