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However, in these solutions, uncertainty in the measurements is taken before classifying a landmark, which results in the incorporation on specific characteristics of the sensor implemented.
The uncertainties related to the standard solutions (uncertainty of P and D in Eqs. (1) and (2)) were not combined into uc because the same reagents were used for both analyses.
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The calculation of solution uncertainty, given input uncertainty, falls under the rubric of uncertainty quantification (UQ).
In order to generate an optimal design solution, uncertainty analysis is also incorporated in this framework.
Consequently, the task of quantifying the resulting solution uncertainty (UQ) is of paramount importance in these simulations.
These parameters are modeled statistically and quantifying the resulting solution uncertainty (UQ) is a crucial task in geophysics.
The solution uncertainty is then dominated by modeling errors governed by the uncertainty of the GFs due to the inaccuracy of the crustal model considered.
The reliability of the assessment of the solution uncertainty by this Bayesian framework depends on the assessment of the data and modeling errors.
We apply modification of the Bayesian full-waveform CMT inversion, ISOLA-ObsPy (Vackář et al. 2017), which allows for reliable assessment of the solution uncertainty.
To summarize this information we compute Highest Posterior-Density (HPD) intervals, and subsequently represent the total solution uncertainty with a probability-box (p-box).
The representations of solution uncertainties, as well as the solutions themselves, are important aspects of the diagram.
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