Markov chain Monte Carlo (McMC) resolves this problem because it enables measurements and the distributions defining their uncertainties to be used as target solutions.
Once agreement with the distributions defining our knowledge of the system is achieved then the quantities sought can be computed concurrently to an accuracy that is dependent only on the quality of the specification of the problem.