Stochastic methods for model assessment of airborne frequency-domain electromagnetic data

@article{Minsley2012StochasticMF,
  title={Stochastic methods for model assessment of airborne frequency-domain electromagnetic data},
  author={Burke J. Minsley and James Irving and Jared D. Abraham and Bruce D. Smith},
  journal={ASEG Extended Abstracts},
  year={2012},
  volume={2012},
  pages={1 - 4}
}
Summary Bayesian Markov chain Monte Carlo (MCMC) algorithms are introduced for the analysis of one- and two-dimensional airborne frequency-domain electromagnetic datasets. Substantial information about parameter uncertainty, non-uniqueness, correlation, and depth of investigation are revealed from the MCMC analysis that cannot be obtained using traditional least-squares methods. In the one-dimensional analysis, a trans-dimensional algorithm allows the number of layers to be unknown, implicitly… 
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