libtasmaniandream8

Tasmanian module for drawing samples from an arbitrary probability distribution

Description

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.

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.

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.

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Homepage

https://github.com/ORNL/TASMANIAN


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