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BIGUQ.jl

Module BIGUQ provides advanced techniques for Uncertainty Quantification, Experimental Design and Decision Analysis based on Bayesian Information Gap Decision Theory (BIGDT).

References:

  • O’Malley, D., Vesselinov, V.V., A combined probabilistic/non-probabilistic decision analysis for contaminant remediation, Journal on Uncertainty Quantification, SIAM/ASA, 10.1137/140965132, 2014.
  • O’Malley, D., Vesselinov, V.V., Bayesian-Information-Gap decision theory with an application to CO2 sequestration, Water Resources Research, 10.1002/2015WR017413, 2015.
  • Grasinger, M., O'Malley, D., Vesselinov, V.V., Karra, S., Decision Analysis for Robust CO2 Injection: Application of Bayesian-Information-Gap Decision Theory, International Journal of Greenhouse Gas Control, 10.1016/j.ijggc.2016.02.017, 2016.

Relevant examples:

BIGUQ.jl module functions:

# BIGUQ.getmcmcchainMethod.

Get MCMC chain

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# BIGUQ.makebigdtsMethod.

Make BIGDT analyses for each possible decision assuming that the proposed observations proposedobs are observed

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# BIGUQ.makebigdtsMethod.

Makes BIGDT analyses for each possible decision assuming that no more observations will be made

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# BIGUQ.BigDTType.

BigOED type

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# BIGUQ.BigOEDType.

BigOED type

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