Example 3: Gaussian Emission lines - correlations
==================================================

In :doc:`example2`, we analysed emission lines. We now have the derived parameters
distribution for each spectrum.

* Are the line widths and heights correlated?
* Are the line heights and positions correlated?
* If yes, what are the parameters of this correlations?

How would you answer these questions?

Keep in mind, that you want to take into account the uncertainties in the
derived parameters!

Next
------

a) For inspiration to the problem above, look at `SysCorr <http://johannesbuchner.github.io/syscorr/index.html>`_ and continue with the example there.
b) Solve the `light-house problem <http://www.gps.caltech.edu/classes/ge193/practicals/practical3/Lighthouse.pdf>`_ with one light house, and with two light houses. Apply model selection!
c) You may want to implement your own problem using pymultinest.

Links
-------
* `jbopt <http://johannesbuchner.github.io/jbopt/index.html>`_ is a cross-algorithm parameter space exploration toolkit. Check out the code example!
* `PyMultiNest documentation <http://johannesbuchner.github.io/pymultinest/index.html>`_
* Also check out pycuba, a Monte Carlo integration library.