.. _faq:
FAQ
===
**The not-so-frequently asked questions that still have useful answers**
What are "walkers"?
-------------------
Walkers are the members of the ensemble. They are almost like separate
Metropolis-Hastings chains but, of course, the proposal distribution for
a given walker depends on the positions of all the other walkers in the
ensemble. See `Goodman & Weare (2010)
`_ for more details.
How should I initialize the walkers?
------------------------------------
The best technique seems to be to start in a small ball around the a priori
preferred position. Don't worry, the walkers quickly branch out and explore
the rest of the space.
Parameter limits
----------------
In order to confine the walkers to a finite volume of the parameter space, have
your function return negative infinity outside of the volume corresponding to
the logarithm of 0 prior probability using
.. code-block:: python
return -numpy.inf