libtasmaniandream8 - 8.1-4 main

The Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN
(Tasmanian) is a collection of robust libraries for high dimensional
integration and interpolation as well as parameter calibration.
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This package provides a shared library that implements the DiffeRential
Evolution Adaptive Metropolis (DREAM), which is a method to draw samples from
an arbitrary probability distribution defined by an arbitrary non-negative
function. The DREAM approach is similar to the classical Markov Chain Monte
Carlo, but it evolves a large number of chains simultaneously which leads to
better parallelization and (potentially) faster convergence. In addition,
multiple chains allow for better exploration of the probability domain, which
is often advantageous when working with multi-modal distributions.
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One of the main applications of DREAM is in the field of Bayesian inference,
where samples are drawn from a posterior distribution comprised from a
data-informed likelihood and an arbitrary model. The DREAM module of Tasmanian
can use Tasmanian Sparse Grids approximation to either the model or the
likelihood.