Blurb::
DREAM (DiffeRential Evolution Adaptive Metropolis) 
Description::

The DiffeRential Evolution Adaptive Metropolis algorithm is described
in \cite Vrugt.  For the DREAM method, one can define the number of
chains used with \c chains (minimum 3). The total number of
generations per chain in DREAM is the number of samples (\c samples)
divided by the number of chains (\c chains).  The number of chains
randomly selected to be used in the crossover each time a crossover
occurs is \c crossover_chain_pairs.  There is an extra adaptation
during burn-in, in which DREAM estimates a distribution of crossover
probabilities that favors large jumps over smaller ones in each of the
chains.  Normalization is required to ensure that all of the input
dimensions contribute equally. In this process, a discrete number of
candidate points for each crossover value is generated. This parameter
is \c num_cr.  The \c gr_threshold is the convergence tolerance for
the Gelman-Rubin statistic which will govern the convergence of the
multiple chain process. The integer \c jump_step forces a long jump
every \c jump_step generations.  For more details about these
parameters, see \cite Vrugt.

<b>Attention: </b> While the \c emulator specification for DREAM
includes the keyword posterior_adaptive, it is not yet operational.

Topics::	bayesian_calibration
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