MUQ  0.02
MUQ Documentation

Welcome to the MUQ (pronounced “muck”) API documentation.


For information on how to build and install MUQ, check out MUQ Installation Guide

Getting started:

MUQ contains several modules for solving Uncertainty Quantification (UQ) related problems. Most of the modules depend on constructing models (either statistical models or process models), so we recommend getting started with MUQ by familiarizing yourself with the Modelling module. With a basic understanding of constructing models, you can start investigating the tools from other modules:

  • Modeling : The modeling module defines classes and methods for constructing both process-based (e.g. physical) and statistical models. Densities, random variables, and forward models can all be defined using the tools in Modelling.
  • SamplingAlgorithms : This module contains tools for sampling probability distributions, including MCMC.
  • Approximation : The approximation module contains a suite of tools for function approximation such as Gaussian processes.
  • Utilities : The utilities module contains general odds an ends needed by the rest of MUQ. Typical tools in the Utilities modules are random number generators and tools for interacting with HDF5 files.

Getting help

MUQ has many features and we know that it can be difficult to find what you are looking for when starting out. We recommend that users start by finding an example that is similar to their problem and adapting the example to suit their needs. If an appropriate example is not available, or you need more information, questions can be posted to MUQ's Q&A site.


Many of the tools in MUQ require manually setting algorithm-specific parameters. In c++, MUQ stores these values in the boost::property_tree:ptree container. In Python, MUQ uses the standard python dict object.