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)

Details

slot 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.

slot dimVarInd:

numeric vector (or NULL) defining the indices of the dimensional variables within slot 'rawData'

slot freqVarInd:

numeric vector (or NULL) defining the indices of the frequency variables within slot 'rawData'

slot numVarInd:

numeric vector (or NULL) defining the indices of the numerical variables within slot 'rawData'

slot weightVarInd:

numeric vector (or NULL) defining the indices of the variables holding weights within slot 'rawData'

slot sampWeightInd:

numeric vector (or NULL) defining the indices of the variables holding sampling weights within slot 'rawData'

slot isMicroData:

logical vector of length 1 (or NULL) that is TRUE if slot 'rawData' are microData and FALSE otherwise

Note

objects of class dataObj are input for slot dataObj in class sdcProblem

Author

Bernhard Meindl bernhard.meindl@statistik.gv.at