Posterior identification of histograms conditional to local data
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Stochastic simulation techniques which do not depend on a back transform step to reproduce a prior marginal cumulative distribution function (cdf)may lead to deviations from that distribution which are deemed unacceptable. This paper presents an algorithm to post process simulated realizations or any spatial distribution to reproduce the target cdfin the case of continuous variables or target proportions in the case of categorical variables, yet honoring the conditioning data. Validations conducted for both continuous and categorical cases show that. by adjusting the value of a correction level parameter ω, the target cdfor proportions can be well reproduced without significant modification of the spatial correlation patterns of the original simulated realizations.
Key wordshistogram reproduction indicator simulation kriging variance conditioning data
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