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| Field |
Value |
| Title: | Random and fuzzy sets in coarse data analysis |
| Authors: | Nguyen, H.T.
吳柏林
Wu, Berlin |
| Contributors: | 應數系 |
| Keywords: | Data reduction; Mathematical models; Probability; Set theory; Statistical methods; Coarse data analysis; Fuzzy statistics; Random fuzzy sets; Random sets; Fuzzy sets |
| Date: | 2006-11 |
| Issue Date: | 2015-07-21 15:29:36 (UTC+8) |
| Abstract: | The theoretical aspects of statistical inference with imprecise data, with focus on random sets, are considered. On the setting of coarse data analysis imprecision and randomness in observed data are exhibited, and the relationship between probability and other types of uncertainty, such as belief functions and possibility measures, is analyzed. Coarsening schemes are viewed as models for perception-based information gathering processes in which random fuzzy sets appear naturally. As an implication, fuzzy statistics is statistics with fuzzy data. That is, fuzzy sets are a new type of data and as such, complementary to statistical analysis in the sense that they enlarge the domain of applications of statistical science. © 2006 Elsevier B.V. All rights reserved. |
| Relation: | Computational Statistics and Data Analysis, 51(1), 70-85 |
| Data Type: | article |
| DOI: | http://dx.doi.org/10.1016/j.csda.2006.04.016 |
| DCField |
Value |
Language |
| dc.contributor (Contributor) | 應數系 | - |
| dc.creator (Authors) | Nguyen, H.T. | - |
| dc.creator (Authors) | 吳柏林 | zh_TW |
| dc.creator (Authors) | Wu, Berlin | en_US |
| dc.date (Date) | 2006-11 | - |
| dc.date.accessioned | 2015-07-21 15:29:36 (UTC+8) | - |
| dc.date.available | 2015-07-21 15:29:36 (UTC+8) | - |
| dc.date.issued (Issue Date) | 2015-07-21 15:29:36 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/76764 | - |
| dc.description.abstract (Abstract) | The theoretical aspects of statistical inference with imprecise data, with focus on random sets, are considered. On the setting of coarse data analysis imprecision and randomness in observed data are exhibited, and the relationship between probability and other types of uncertainty, such as belief functions and possibility measures, is analyzed. Coarsening schemes are viewed as models for perception-based information gathering processes in which random fuzzy sets appear naturally. As an implication, fuzzy statistics is statistics with fuzzy data. That is, fuzzy sets are a new type of data and as such, complementary to statistical analysis in the sense that they enlarge the domain of applications of statistical science. © 2006 Elsevier B.V. All rights reserved. | - |
| dc.format.extent | 285843 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (Relation) | Computational Statistics and Data Analysis, 51(1), 70-85 | - |
| dc.subject (Keywords) | Data reduction; Mathematical models; Probability; Set theory; Statistical methods; Coarse data analysis; Fuzzy statistics; Random fuzzy sets; Random sets; Fuzzy sets | - |
| dc.title (Title) | Random and fuzzy sets in coarse data analysis | - |
| dc.type (Data Type) | article | en |
| dc.identifier.doi (DOI) | 10.1016/j.csda.2006.04.016 | - |
| dc.doi.uri | http://dx.doi.org/10.1016/j.csda.2006.04.016 | - |
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