diff --git a/doc/source/faq.rst b/doc/source/faq.rst index bd0f626..5197bf7 100644 --- a/doc/source/faq.rst +++ b/doc/source/faq.rst @@ -16,6 +16,7 @@ asked. - :ref:`Are ctools and GammaLib specific to CTA? ` - :ref:`I want to upgrade ctools, do I have to upgrade GammaLib? ` - :ref:`Why does my ctool complain about missing parameters? ` +- :ref:`Should I used binned or unbinned analysis? ` .. _faq_ctools_gammalib: @@ -96,3 +97,25 @@ asked. your pfiles folder. Simply erasing all files in the pfiles folder should fix this problem. + +.. _faq_analysis: + +.. topic:: Should I used binned or unbinned analysis? + + This depends on the amount of data you want to analyse and to some extent + on the question you want to answer with your analysis. + For an unbinned analysis, the computation time increases about linearly + with the number of events and hence with the duration of the observation, + while for binned analysis the computation time depends only on the number + of bins that is used. + Consequently, for short observation times (below 30 hours), unbinned + analysis is faster, while for longer times it is advantageous to use + a binned analysis. + If you want to take the energy dispersion into account (which is required + if your analysis covers the lowest energies), you need to use unbinned + analysis, since binned analysis does not yet implement energy dispersion. + If you'd like to fit a Gaussian line to your data you may also prefer + unbinned over binned analysis, as the fine sampling required to resolve + the line may require a prohibitive large number of energy bins for a binned + analysis. + diff --git a/doc/source/issues.rst b/doc/source/issues.rst index 002400f..d56c6b6 100644 --- a/doc/source/issues.rst +++ b/doc/source/issues.rst @@ -41,8 +41,7 @@ Below you will find a list of known issues. When performing a binned or stacked analysis you should make sure that the spatial and spectral binning is sufficiently fine grained. The spatial binning should be better than the best angular resolution - over the energy range of interest. Use a typical value of 0.02 degrees. - For the spectral binning, use at least 5 bins per decade. - If the binning is too coarse, the spectral parameters will be biased. - For example, a spectral hardening is observed when using a coarser - spatial binning. + over the energy range of interest. Use a typical value of 0.02 degrees + per pixel for the spatial binning and 10 bins per decade for the + spectral binning. If the binning is too coarse, the spectral parameters + that are fitted will be biased.