PDF --- Basic PDFs ########## Basic shapes are fundamental PDFs, with often well-known functional form. They are usually fully analytically implemented and often a thin wrapper around :py:class:`~tensorflow_probability.distribution.Distribution`. Any missing shape can be easily wrapped using :py:class:`~zfit.pdf.WrapDistribution`. .. toctree:: :maxdepth: 2 pdf/basic Binned PDFs ########### Binned PDFs extend the functionality of unbinned PDFs by providing more histogram-like features in addition to the basic unbinned PDFs. They interface with the `Unified Histogram Interface (uhi) `_ that is provided `boost-histogram `_ and especially `Hist `_. .. toctree:: :maxdepth: 2 pdf/binned_pdf Polynomials ############# While polynomials are also basic PDFs, they convey mathematically a more special class of functions. They constitute a sum of different degrees. .. toctree:: :maxdepth: 2 pdf/polynomials Kernel Density Estimations ############################# KDEs provide a means of non-parametric density estimation. An extensive introduction and explanation can be found in :ref:`sec-kernel-density-estimation`. .. toctree:: :maxdepth: 2 pdf/kde_api Composed PDFs ############################# Composed PDFs build on top of others and provide sums, products and more. .. toctree:: :maxdepth: 2 pdf/composed_pdf Custom base class ############################# These base classes are used internally to build PDFs and can also be used to implement custom PDFs. They offer more or less support and freedom. .. toctree:: :maxdepth: 2 pdf/custom_base Physics PDFs ############## Physics PDFs are PDFs that are often used in high energy physics. They are in the zfit-physics package, which needs to be installed separately. .. toctree:: :maxdepth: 2 pdf/physics