Résumé
The book provides a generalization of Gaussian error
intervals to situations where the data follow non-Gaussian
distributions. This usually occurs in frontier science,
where the observed parameter is just above background or
the histogram of multiparametric data contains empty
bins.
Then the validity of a theory cannot be decided by the
chi-squared-criterion, but this long-standing problem is
solved here. The book is based on Bayes' theorem, symmetry
and differential geometry.
In addition to solutions of practical problems, the text
provides an epistemic insight: The logic of quantum
mechanics is obtained as the logic of unbiased inference
from counting data. However, no knowledge of quantum
mechanics is required.
The text, examples and exercises are written at an
introductory level.
Contents
- Knowledge and Logic
- Bayes' Theorem
- Probable and improbable Data
- Description of Distributions I: Real x
- Description of Distributions II Natural x
- Form Invariance I: Real x
- Examples of Invariant Measures
- A Linear Representation of Form Invariance
- Beyond Form Invariance: The Geometric Prior
- Inferring the Mean or Standard Deviation
- Form Invariance II: Natural x
- Independence of Parameters
- The Art of Fitting I: Real x
- Judging a Fit I: Real x
- The Art of Fitting II: Natural x
- Judging a Fit II: Natural x
- Summary
- Appendices
- References
- Index
L'auteur - H.L. Harney
Max Planck Institut für Kernphysik, Heidelberg, Germany
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Springer |
| Auteur(s) | H.L. Harney |
| Parution | 02/06/2003 |
| Nb. de pages | 276 |
| Format | 16 x 24 |
| Couverture | Relié |
| Poids | 637g |
| Intérieur | Noir et Blanc |
| EAN13 | 9783540003977 |
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