dc.contributor.author |
Zaikin A. |
|
dc.date.accessioned |
2020-01-22T20:32:12Z |
|
dc.date.available |
2020-01-22T20:32:12Z |
|
dc.date.issued |
2019 |
|
dc.identifier.issn |
0040-585X |
|
dc.identifier.uri |
https://dspace.kpfu.ru/xmlui/handle/net/157924 |
|
dc.description.abstract |
© 2019 Society for Industrial and Applied Mathematics. The definition of a decision function with asymptotically (n →∞) uniformly minimal d-risk is presented in the framework of the general theory of statistical inference. Using this definition, we prove that the maximum likelihood estimate has asymptotically uniformly minimal d-risk. This extends one result by I. N. Volodin and A. A. Novikov [Theory Probab. Appl., 38 (1994), pp. 118–128] for shrinking priors to the general class of continuous distributions. The proof uses the asymptotic representation of the posterior risk function, as obtained in [A. A. Zaikin, J. Math. Sci. (N.Y.), 229 (2018), pp. 678–697]. |
|
dc.relation.ispartofseries |
Theory of Probability and its Applications |
|
dc.subject |
D-risk |
|
dc.subject |
Maximum likelihood estimate |
|
dc.subject |
Posterior risk asymptotics |
|
dc.title |
Estimates with asymptotically uniformly minimal d-risk |
|
dc.type |
Article |
|
dc.relation.ispartofseries-issue |
3 |
|
dc.relation.ispartofseries-volume |
63 |
|
dc.collection |
Публикации сотрудников КФУ |
|
dc.relation.startpage |
500 |
|
dc.source.id |
SCOPUS0040585X-2019-63-3-SID85064694652 |
|