Example 3: Gaussian Emission lines - correlations
In Example 2: Gaussian Emission lines, 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
- For inspiration to the problem above, look at SysCorr and continue with the example there.
- Solve the light-house problem with one light house, and with two light houses. Apply model selection!
- You may want to implement your own problem using pymultinest.
Links
- jbopt is a cross-algorithm parameter space exploration toolkit. Check out the code example!
- PyMultiNest documentation
- Also check out pycuba, a Monte Carlo integration library.