| 书目名称 | Statistical Inference and Prediction in Climatology |
| 副标题 | A Bayesian Approach |
| 编辑 | Edward S. Epstein |
| 视频video | |
| 概述 | Written by experts, Peer reviewed, Comprehensive in scope |
| 丛书名称 | Meteorological Monographs |
| 图书封面 |  |
| 描述 | The climatologist (like the hydrologist, the economist, the social scientist, and others) is frequently faces with situations in which a prediction must be made of the outcome of a process that is inherently probabilistic, and this inherent uncertainty is compounded by the expert‘s limited knowledge of the process itself. An example might be predicting next summer‘s mean temperature at a previously unmonitored location. This monograph deals with the balanced use of expert judgment and limited data in such situations. How does the expert quantify his or her judgment? When data are plentiful they can tell a complete story, but how does one alter prior judgment in the light of a few observations, and integrate that information into a consistent and knowledgeable prediction? Bayes theorem provides a straightforward rule for modifying a previously held belief in the light of new data. Bayesian methods are valuable and practical. This monograph is intended to introduce some concepts of statistical inference and prediction that are not generally treated in the traditional college course in statistics, and have not seen their way into the technical literature generally available to the pra |
| 出版日期 | Book 1985 |
| 关键词 | Statistics; Statistical inference; Forecast techniques; Bernoulli and Poisson processes; fundamentals of |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-935704-27-0 |
| isbn_ebook | 978-1-935704-27-0Series ISSN 0065-9401 |
| issn_series | 0065-9401 |
| copyright | American Meteorological Society 1985 |
发表于 2025-3-21 16:57:45
