ISBN: 9789812383563 - bayesian reasoning in data analysis: a critical introduction (3 Ergebnisse)

- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 152,38
EUR 14,96 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 2 verfügbar
Hardcover. Zustand: Brand New. 329 pages. 9.00x6.00x0.75 inches. In Stock.

- Hardcover
Anbieter: moluna, Greven, Deutschlandmoluna
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 152,07
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Zustand: New. A multi-level introduction to Bayesian reasoning. The basic ideas of this approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference combination of results.

Sprache: Englisch
Verlag: World Scientific Publishing Company Jun 2003, 2003
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 203,69
EUR 35,00 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Buch. Zustand: Neu. Neuware - This book provides a multi-level introduction to Bayesian reasoning (as opposed to 'conventional statistics') and its applications to data analysis. The basic ideas of this 'new' approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide -- under well-defined assumptions! -- with 'standard' methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework.…