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Inferential Models: Reasoning with Uncertainty - Chapman & Hall / CRC Monographs on Statistics and Applied Probability Ryan Martin 第1 版
Inferential Models: Reasoning with Uncertainty - Chapman & Hall / CRC Monographs on Statistics and Applied Probability
Ryan Martin
A New Approach to Sound Statistical Reasoning
Inferential Models: Reasoning with Uncertainty introduces the authors? recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The authors show how an IM produces meaningful prior-free probabilistic inference at a high level.
The book covers the foundational motivations for this new IM approach, the basic theory behind its calibration properties, a number of important applications, and new directions for research. It discusses alternative, meaningful probabilistic interpretations of some common inferential summaries, such as p-values. It also constructs posterior probabilistic inferential summaries without a prior and Bayes? formula and offers insight on the interesting and challenging problems of conditional and marginal inference.
This book delves into statistical inference at a foundational level, addressing what the goals of statistical inference should be. It explores a new way of thinking compared to existing schools of thought on statistical inference and encourages you to think carefully about the correct approach to scientific inference.
276 pages, 37 black & white illustrations, 10 black & white tables
| メディア | 書籍 Hardcover Book (ハードカバー付きの本) |
| リリース済み | 2015年9月25日 |
| ISBN13 | 9781439886489 |
| 出版社 | Taylor & Francis Inc |
| ページ数 | 256 |
| 寸法 | 241 × 165 × 21 mm · 590 g |
| 言語 | 英語 |
