Vai al contenuto principale della pagina

Bayesian Inference : Data Evaluation and Decisions / / by Hanns Ludwig Harney



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Harney Hanns Ludwig Visualizza persona
Titolo: Bayesian Inference : Data Evaluation and Decisions / / by Hanns Ludwig Harney Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Edizione: 2nd ed. 2016.
Descrizione fisica: 1 online resource (XIII, 243 p. 39 illus., 3 illus. in color.)
Disciplina: 530.15
Soggetto topico: Physics
Statistics 
Nuclear physics
Probabilities
Medical physics
Radiation
Computer mathematics
Mathematical Methods in Physics
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Particle and Nuclear Physics
Probability Theory and Stochastic Processes
Medical and Radiation Physics
Computational Mathematics and Numerical Analysis
Note generali: Includes index.
Nota di contenuto: Knowledge an Logic -- Bayes' Theorem -- Probable and Improbable Data -- Descriptions of Distributions I: Real x -- Description of Distributions II: Natural x -- Form Invariance I -- Examples of Invariant Measures -- A Linear Representation of Form Invariance -- Going Beyond Form Invariance: The Geometric Prior -- Inferring the Mean or Standard Deviation -- Form Invariance II: Natural x -- Item Response Theory -- On the Art of Fitting -- Problems and Solutions -- Description of Distributions I -- Real x -- Form Invariance I -- Beyond Form Invariance: The Geometric Prior -- Inferring Mean or Standard Deviation -- Form Invariance II: Natural x -- Item Response Theory -- On the Art of Fitting. .
Sommario/riassunto: This new edition offers a comprehensive introduction to the analysis of data using Bayes rule. It generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. This is particularly useful when the observed parameter is barely above the background or the histogram of multiparametric data contains many empty bins, so that the determination of the validity of a theory cannot be based on the chi-squared-criterion. In addition to the solutions of practical problems, this approach provides an epistemic insight: the logic of quantum mechanics is obtained as the logic of unbiased inference from counting data. New sections feature factorizing parameters, commuting parameters, observables in quantum mechanics, the art of fitting with coherent and with incoherent alternatives and fitting with multinomial distribution. Additional problems and examples help deepen the knowledge. Requiring no knowledge of quantum mechanics, the book is written on introductory level, with many examples and exercises, for advanced undergraduate and graduate students in the physical sciences, planning to, or working in, fields such as medical physics, nuclear physics, quantum mechanics, and chaos.
Titolo autorizzato: Bayesian inference  Visualizza cluster
ISBN: 3-319-41644-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910136019303321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui