Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/120185
DC Field | Value | Language |
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dc.contributor | 應數系 | |
dc.creator | Dickey, James M. | |
dc.creator | 姜志銘 | |
dc.creator | Jiang, Thomas J. | |
dc.date | 1998 | |
dc.date.accessioned | 2018-09-27T09:26:18Z | - |
dc.date.available | 2018-09-27T09:26:18Z | - |
dc.date.issued | 2018-09-27T09:26:18Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/120185 | - |
dc.description.abstract | We develop prior distributions for histogram inference favoring smooth population frequencies; that is, probability vectors with small differences for neighboring categories. We give a theory of prior-random probability vectors representable as a linear transform, or “filter,” of a standard random probability vector, or equivalently, a random weighted average of nonrandom smooth probability vectors. Promising methods of prior assessment are given based on elicitation of a list of typically smooth probability vectors, the empirical moments of which can then be matched by the mean vector and variance matrix of a constructed continuous-type filtered-variate prior distribution. | en_US |
dc.format.extent | 130 bytes | - |
dc.format.mimetype | text/html | - |
dc.relation | Journal of the American Statistical Association, 93:442, 651-662 | |
dc.subject | Bayesian smoothing; Carlson function; Generalized Dirichlet distribution; Generalized hypergeometric function; Multinomial distribution; Multinomial estimation. | |
dc.title | Filtered-variate prior distributions for histogram smoothing. | |
dc.type | article | |
dc.identifier.doi | 10.1080/01621459.1998.10473718 | |
dc.doi.uri | https://doi.org/10.1080/01621459.1998.10473718 | |
item.grantfulltext | restricted | - |
item.openairetype | article | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | 期刊論文 |
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