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Imprecision in statistical data analysis

Different sources of imprecision in connection with both empirical data (especially linguistic data, expert opinions/judgments/perceptions, as well as various kinds of ill-observed statistical data) and/or models may arise in statistical data analysis. Applications are found in different sciences, as Economics, Biomedicine, Bioinformatics, Ecology, Geology, etc. to manage complex problems involving heterogeneous information. Special (but not exclusive) topics are regression, cluster analysis and statistical inference with (fuzzy) set-valued data, belief functions, random sets or imprecise probability models. In spite of the impact of this growing literature, there is room for further developments in several directions, including methods, computation and applications of the use of imprecision in Statistics.

M. Angeles Gil, University of Oviedo, Spain. Pedro Teran, University of Oviedo, Spain.
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