The Parallel C++ Statistical Library ‘QUESO’: Quantification of Uncertainty for Estimation, Simulation and Optimization

  • Ernesto E. Prudencio
  • Karl W. Schulz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7155)


QUESO is a collection of statistical algorithms and programming constructs supporting research into the uncertainty quantification (UQ) of models and their predictions. It has been designed with three objectives: it should (a) be sufficiently abstract in order to handle a large spectrum of models, (b) be algorithmically extensible, allowing an easy insertion of new and improved algorithms, and (c) take advantage of parallel computing, in order to handle realistic models. Such objectives demand a combination of an object-oriented design with robust software engineering practices. QUESO is written in C++, uses MPI, and leverages libraries already available to the scientific community. We describe some UQ concepts, present QUESO, and list planned enhancements.


Software Design Uncertainty Quantification Parallel MCMC 


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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ernesto E. Prudencio
    • 1
  • Karl W. Schulz
    • 1
  1. 1.Institute for Computational Engineering and Sciences (ICES)The University of TexasAustinUSA

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