| 书目名称 | Specifying Statistical Models |
| 副标题 | From Parametric to N |
| 编辑 | J. P. Florens,M. Mouchart,A. F. M. Smith |
| 视频video | |
| 丛书名称 | Lecture Notes in Statistics |
| 图书封面 |  |
| 描述 | During the last decades. the evolution of theoretical statistics has been marked by a considerable expansion of the number of mathematically and computationaly trac table models. Faced with this inflation. applied statisticians feel more and more un comfortable: they are often hesitant about their traditional (typically parametric) assumptions. such as normal and i. i. d . • ARMA forms for time-series. etc . • but are at the same time afraid of venturing into the jungle of less familiar models. The prob lem of the justification for taking up one model rather than another one is thus a crucial one. and can take different forms. (a) ~~~£ifi~~~iQ~ : Do observations suggest the use of a different model from the one initially proposed (e. g. one which takes account of outliers). or do they render plau sible a choice from among different proposed models (e. g. fixing or not the value of a certai n parameter) ? (b) tlQ~~L~~l!rQ1!iIMHQ~ : How is it possible to compute a "distance" between a given model and a less (or more) sophisticated one. and what is the technical meaning of such a "distance" ? (c) BQe~~~~~~ : To what extent do the qualities of a procedure. well adapted to a "small" |
| 出版日期 | Conference proceedings 1983 |
| 关键词 | Bayessches Verfahren; Statistik; bayesian statistics; best fit; principal component analysis |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4612-5503-1 |
| isbn_softcover | 978-0-387-90809-0 |
| isbn_ebook | 978-1-4612-5503-1Series ISSN 0930-0325 Series E-ISSN 2197-7186 |
| issn_series | 0930-0325 |
| copyright | Springer Science+Business Media New York 1983 |
发表于 2025-3-21 17:06:24
