Finding nonlinear data dependencies

Question

I have a multidimensional array of data (x1,x2,x3,...,y). There are no information about data correlation, nature and boundaries. I have performed some analyses to find linear dependence using regression but nothing were found.

I would like try to find non-linear dependence. I haven't found any information how to perform the analysis if I just have portion of data. Which methods and/or algorithms can I use to find dependence of data?

Given two vectors x and y you can always find a function y=f(x). So all the variables are nonlinear dependent. You should limit the kind of non linearity that you want to consider — Donbeo, May 26 '14 at 15:49
Ok. For example I would like to find non linearity of 3 values (y = f(x1,x2,x3)) - how can I find the dependence? — Yurei, May 26 '14 at 16:18
There are thousands of techniques. I suggest you to give a look to the book "the elements of statistical learning" — Donbeo, May 26 '14 at 16:19
I'd consider this question both too broad (since there are infinitely many kinds of function to be considered) and off topic (because this is about [statistics](http://stats.stackexchange.com/) not programming). I'll vote to close once I've made up my mind between these two possible reasons. — MvG, May 26 '14 at 18:06
This question appears to be off-topic because it is about statistics — MvG, May 26 '14 at 20:03

score 0 · Answer 1 · answered May 27 '14 at 01:16

The general topic you are looking for has various names. Search for "nonlinear regression" and "data mining" and "machine learning". I second the recommendation for Hastie & Tibshirani, "Elements of Statistical Learning". Brian Ripley also has a good book on the topic; I don't remember the title. There are probably many more good books.

If you can give more details about the problem, maybe someone has more specific advice. Probably it's better to take it to the StackExchange statistics forum rather than StackOverflow.

Finding nonlinear data dependencies

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