This class models a data object containing the 'raw' data for a given problem as well as information on the position of the dimensional variables, the count variable, additional numerical variables, weights or sampling weights within the raw data. Also slot 'isMicroData' shows if slow 'rawData' consists of microdata (multiple observations for each cell are possible, isMicroData==TRUE) or if data have already been aggregated (isMicroData==FALSE)
rawData:list with each element being a vector of either codes of dimensional variables, counts, weights that should be used for secondary cell suppression problem, numerical variables or sampling weights.
dimVarInd:numeric vector (or NULL) defining the indices of the dimensional variables within slot 'rawData'
freqVarInd:numeric vector (or NULL) defining the indices of the frequency variables within slot 'rawData'
numVarInd:numeric vector (or NULL) defining the indices of the numerical variables within slot 'rawData'
weightVarInd:numeric vector (or NULL) defining the indices of the variables holding weights within slot 'rawData'
sampWeightInd:numeric vector (or NULL) defining the indices of the variables holding sampling weights within slot 'rawData'
isMicroData:logical vector of length 1 (or NULL) that is TRUE if slot 'rawData' are microData and FALSE otherwise
objects of class dataObj are input for slot dataObj in class sdcProblem