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Update musoRand.R

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Zoltán BARCZA 2019-01-24 22:20:25 +01:00 committed by GitHub
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RBBGCMuso/R/musoRand.R
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#' musoRand #' musoRand
#' #'
#' This funtion samples uniformly from the choosen parameters of the BiomeBGC-Muso model, which parameters are constrained by the model logic. #' This funtion samples uniformly from the chosen parameters of the Biome-BGCMuSo model, where the parameters are constrained by the model logic.
#' @author Roland Hollos #' @author Roland Hollos
#' @param parameters This is a dataframe (heterogen data-matrix), which first column is the name of the parameters, the second is a numeric vector of the rownumbers of the given variable in the input-file, the last two column consist the endpont of the parameter-ranges, where the parameters will be randomized. #' @param parameters This is a dataframe (heterogeneous data-matrix), where first column is the name of the parameters, the second is a numeric vector of the rownumbers of the given variable in the input-file, the last two column consist the endpont of the parameter-ranges, where the parameters will be randomized.
#' @param constrains This is a matrics wich specify the constrain rules for the sampling. Further informations coming son. #' @param constrains This is a matrics wich specify the constrain rules for the sampling. Further informations coming son.
#' @param iteration The number of sample-s. It is adviced to use at least 3000 iteration, because it is generally fast and it can be subsampled later at any time. #' @param iteration The number of samples. We propose to use at least 3000 iteration, because it is generally fast and it can be subsampled later at any time.
#' @importFrom limSolve xsample #' @importFrom limSolve xsample
#' @export #' @export