martes, 9 de diciembre de 2008

dealing with data in a different way


(simplifying) statistical methods, although being based, in general, on sensible assumptions, imply an uncertainty, accepted until the moment as the less worse solution, but still is this the case?
nowadays, any home computer can easily perform calculations, difficult to be imagined just 10 ago. then? why simplifying further?

trendingBot offers an alternative path based on the following ideas:
1. simplifications = possible errors
2. the most complex situation can be divided into simpler behaviours
3. any of these behaviours can be mathematically described by selecting the appropriate variables
- error in the predictions means wrong variable selection
- any arbitrary user intervention (user-defined parameters) means wrong model delimitation
4. the most of the "natural" behaviours are based on quite simple mathematical relations
5. more detailed means better => combinatorics better than simplifying statical methods