The work addresses a very common problem: finding the main underlying factors behind a chuck of data. The particular point here is that we take care of the situations when the elements of your data vectors are attributes in special domains. I.e. sometime you have good reasons NOT to consider all of them just general real numbers (then your next step is to claim the population is Gaussian and march on …), but positive-only, binary, etc. We find major components for those data AND consider the problem of choosing how many components to use.