Automatic random variate generation in Python
Tirth Patel
The generation of random variates is an important tool that is required in
many applications. Various software programs or packages contain generators
for standard distributions like the normal, exponential or Gamma, e.g., the
programming language R and the packages SciPy and NumPy in Python. However,
it is not uncommon that sampling from new/non-standard distributions is
required. Instead of deriving specific generators in such situations,
so-called automatic or black-box methods have been developed. These allow
the user to generate random variates from fairly large classes of
distributions by only specifying some properties of the distributions (e.g.
the density and/or cumulative distribution function). In this note, we
describe the implementation of such methods from the C library UNU.RAN in
the Python package SciPy and provide a brief overview of the functionality.
numerical inversion, generation of random variates
DOI10.25080/majora-212e5952-007