Name
Abstract | ||
|---|---|---|
The main subject of this paper is the embedding of fuzzy set theory-and related concepts-in a coherent conditional probability scenario. This allows to deal with perception-based information-in the sense of Zadeh-and with a rigorous treatment of the concept of likelihood, dealing also with its role in statistical inference. A coherent conditional probability is looked on as a general non-additive ''uncertainty'' measure m(.)=P(E|.) of the conditioning events. This gives rise to a clear, precise and rigorous mathematical frame, which allows to define fuzzy subsets and to introduce in a very natural way the counterparts of the basic continuous T-norms and the corresponding dual T-conorms, bound to the former by coherence. Also the ensuing connections of this approach to possibility theory and to information measures are recalled. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.csda.2006.04.028 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
coherent conditional probability,rigorous treatment,fuzzy set theory-and,perception-based information,conditioning event,fuzzy subsets,general non-additive,likelihood function,fuzzy information,basic continuous t-norms,fuzzy theory,corresponding dual t-conorms,coherent conditional probability scenario,rigorous mathematical frame,statistical inference,possibility theory,conditional probability,fuzzy set theory | Conditional probability distribution,Conditional probability,Probability measure,Possibility theory,Posterior probability,Probability distribution,Regular conditional probability,Statistics,Conditional mutual information,Mathematics,Calculus | Journal |
Volume | Issue | ISSN |
51 | 1 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
20 | 1.41 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giulianella Coletti | 1 | 572 | 71.49 |
| Romano Scozzafava | 2 | 367 | 48.05 |