Matches in UGent Biblio for { <https://biblio.ugent.be/publication/320871#aggregation> ?p ?o. }
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- aggregation classification "P1".
- aggregation creator person.
- aggregation creator person.
- aggregation date "2005".
- aggregation format "application/pdf".
- aggregation hasFormat 320871.bibtex.
- aggregation hasFormat 320871.csv.
- aggregation hasFormat 320871.dc.
- aggregation hasFormat 320871.didl.
- aggregation hasFormat 320871.doc.
- aggregation hasFormat 320871.json.
- aggregation hasFormat 320871.mets.
- aggregation hasFormat 320871.mods.
- aggregation hasFormat 320871.rdf.
- aggregation hasFormat 320871.ris.
- aggregation hasFormat 320871.txt.
- aggregation hasFormat 320871.xls.
- aggregation hasFormat 320871.yaml.
- aggregation language "eng".
- aggregation publisher "International Society for Imprecise Probability: Theories and Applications (SIPTA)".
- aggregation rights "I have retained and own the full copyright for this publication".
- aggregation subject "Mathematics and Statistics".
- aggregation title "Imprecise probability models for inference in exponential families".
- aggregation abstract "When considering sampling models described by a distribution from an exponential family, it is possible to create two types of imprecise probability models. One is based on the corresponding conjugate distribution and the other on the corresponding predictive distribution. In this paper, we show how these types of models can be constructed for any (regular, linear, canonical) exponential family, such as the centered normal distribution. To illustrate the possible use of such models, we take a look at credal classification. We show that they are very natural and potentially promising candidates for describing the attributes of a credal classifier, also in the case of continuous attributes.".
- aggregation authorList BK193922.
- aggregation endPage "296".
- aggregation startPage "287".
- aggregation aggregates 559483.
- aggregation isDescribedBy 320871.
- aggregation similarTo LU-320871.