| Автор | SWEETING, TREVOR J. |
| Дата выпуска | 1995 |
| dc.description | SUMMARYSweeting (1995) studies regular Bayesian and frequentist approximations within a unified framework in the case of a single parameter, and shows that higher-order approximations to sampling distributions arise from their Bayesian counterparts via an unsmoothing argument. In the present paper we extend this programme to include formulae in approximate conditional inference. In particular it is shown how Bayesian arguments may be used to derive some formulae developed by Barndorff-Nielsen (1980, 1983, 1986). The development proceeds in terms of likelihood roots. |
| Формат | application.pdf |
| Издатель | Oxford University Press |
| Копирайт | © 1995 Biometrika Trust |
| Тема | Approximate Bayesian inference |
| Тема | Approximate conditional inference |
| Тема | Kullback-Leibler distance |
| Тема | Likelihood root |
| Тема | Local ancillarity |
| Тема | Unsmoothing |
| Тема | Articles |
| Название | A Bayesian approach to approximate conditional inference |
| Тип | research-article |
| Electronic ISSN | 1464-3510 |
| Print ISSN | 0006-3444 |
| Журнал | Biometrika |
| Том | 82 |
| Первая страница | 25 |
| Последняя страница | 36 |
| Аффилиация | Department of Mathematical and Computing Sciences, University of SurreyGuildford GU2 5XH, U. K. |
| Выпуск | 1 |
