| dc.contributor | 應用數學系 | - |
| dc.creator (作者) | Jiang, Thomas J. | - |
| dc.creator (作者) | 姜志銘 | zh_TW |
| dc.creator (作者) | Song, C.-C. | en_US |
| dc.creator (作者) | Kuo, K.-L. | zh_TW |
| dc.date (日期) | 2017-05 | - |
| dc.date.accessioned | 8-May-2017 14:43:03 (UTC+8) | - |
| dc.date.available | 8-May-2017 14:43:03 (UTC+8) | - |
| dc.date.issued (上傳時間) | 8-May-2017 14:43:03 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/109342 | - |
| dc.description.abstract (摘要) | A conditional model is a set of conditional distributions, which may be compatible or incompatible, depending on whether or not there exists a joint distribution whose conditionals match the given conditionals. In this paper, we propose a new mathematical tool called a “structural ratio matrix” (SRM) to develop a unified compatibility approach for discrete conditional models. With this approach, we can find all joint pdfs after confirming that the given model is compatible. In practice, it is most likely that the conditional models we encounter are incompatible. Therefore, it is important to investigate approximated joint distributions for them. We use the concept of SRM again to construct an almost compatible joint distribution, with consistency property, to represent the given incompatible conditional model. © 2017 Elsevier Inc. | - |
| dc.format.extent | 431493 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Journal of Multivariate Analysis, 157, 115-123 | - |
| dc.title (題名) | Exactly and almost compatible joint distributions for high-dimensional discrete conditional distributions | - |
| dc.type (資料類型) | article | - |
| dc.identifier.doi (DOI) | 10.1016/j.jmva.2017.03.005 | - |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1016/j.jmva.2017.03.005 | - |
