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.
Full papers containing a strong computational or data analytic component will be considered for publication in the journal Computational Statistics and Data Analysis. All submissions must contain original unpublished work not being considered for publication elsewhere. Submissions will be refereed according to standard procedures for CSDA.