My programs are closer to time-series analysis and pattern analysis than combinatorics.
More specifically:
The program looks for
all occurances of sub sequences of numbers, n1, n2, ... nm
in a main sequence, n0 ... mz
where n1< n2< ... nm
and then calculates the probability of each sequence.
The goal is not to find a specific sub sequence, but to find downward trends.
The program can be used to predict the next number:
E.g. If you have observed that the last 3 numbers were: n1< n2< n3
then the program will tell you the probability that the next number in the sequence will be n0.
You can also specify a minimum value for n0.
E.g. If you want to predict when a share price will drop low enough to make it worth buying.
The program can be used to find underlying cycles:
If data is smoothed with some algorithm and plotted, then it is easy to see peaks and valleys.But to calculate the periods more precisely is difficult especially if the periods are not exact and if you are using big datasets.
The program will calculate a numerical value for the periods.
