| Titre : |
Practical Bayesian Inference : A Primer for Physical Scientists |
| Type de document : |
texte imprimé |
| Auteurs : |
Coryn A. L. Bailer-Jones, Auteur |
| Editeur : |
Cambridge ; New York ; Melbourne [UK ; USA] : Cambridge University Press (CUP) |
| Année de publication : |
2017 |
| Importance : |
1 vol. (IX, 295 p.) |
| Présentation : |
ill. |
| Format : |
26 cm |
| ISBN/ISSN/EAN : |
978-1-107-19211-9 |
| Note générale : |
ISBN : 978-1-107-19211-9 (hbk. :; alk. paper). - 1-107-19211-0 (hbk. : alk. paper). - 978-1-316-64221-4 (pbk. : alk. paper). - 1-316-64221-6 (pbk. : alk. paper). -- PPN 204365279 |
| Langues : |
Anglais (eng) |
| Tags : |
Statistique bayésienne Physique mathématique Bayesian statistical decision theory Mathematical physics |
| Index. décimale : |
519.542 Théorie de la décision (statistique mathématique dont statistique bayésienne) |
| Résumé : |
"Science is fundamentally about learning from data, and doing so in the presence of uncertainty. Uncertainty arises inevitably and avoidably in many guises. It comes from noise in our measurements: we cannot measure exactly. It comes from sampling effects: we cannot measure everything. It comes from complexity: data may be numerous, high dimensional, and correlated, making it difficult to see structures. This book is an introduction to statistical methods for analysing data. It presents the major concepts of probability and statistics as well as the computational tools we need to extract meaning from data in the presence of uncertainty" (site de l'éditeur) |
| Note de contenu : |
Bibliogr. p. 289-209.Index |
Practical Bayesian Inference : A Primer for Physical Scientists [texte imprimé] / Coryn A. L. Bailer-Jones, Auteur . - Cambridge ; New York ; Melbourne (UK ; USA) : Cambridge University Press (CUP), 2017 . - 1 vol. (IX, 295 p.) : ill. ; 26 cm. ISBN : 978-1-107-19211-9 ISBN : 978-1-107-19211-9 (hbk. :; alk. paper). - 1-107-19211-0 (hbk. : alk. paper). - 978-1-316-64221-4 (pbk. : alk. paper). - 1-316-64221-6 (pbk. : alk. paper). -- PPN 204365279 Langues : Anglais ( eng)
| Tags : |
Statistique bayésienne Physique mathématique Bayesian statistical decision theory Mathematical physics |
| Index. décimale : |
519.542 Théorie de la décision (statistique mathématique dont statistique bayésienne) |
| Résumé : |
"Science is fundamentally about learning from data, and doing so in the presence of uncertainty. Uncertainty arises inevitably and avoidably in many guises. It comes from noise in our measurements: we cannot measure exactly. It comes from sampling effects: we cannot measure everything. It comes from complexity: data may be numerous, high dimensional, and correlated, making it difficult to see structures. This book is an introduction to statistical methods for analysing data. It presents the major concepts of probability and statistics as well as the computational tools we need to extract meaning from data in the presence of uncertainty" (site de l'éditeur) |
| Note de contenu : |
Bibliogr. p. 289-209.Index |
|
Practical Bayesian Inference (2017)