Linguistic Summaries in Small Area Statistics
Data collection in small area statistics also copes with missing values. In the municipal statistics we can recognize more or less similar municipalities and more or less dependent indicators. Therefore, an approach capable to process this uncertainty is desirable. Data produced in small area statistics are valuable source for users. Data dissemination which mimics human reasoning in searching and evaluation data could be a suitable solution. Thus, there is a space for improving both processes by linguistic summaries which are based on fuzzy logic. Finally, the paper discusses future research and development topics in this field.
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