Open AccessBook
Bayesian Statistical Modelling
Peter Congdon
- 02 May 2001
TL;DR: In this article, Congdon's Bayesian Statistical Modelling is used as a reference source for Bayesian models and literature, and a large number of models, e.g., for standard distributions, classification, regression, hierarchical pooling of information, missing data, correlated data, multivariate data, time series, spatial data, longitudinal data, measurement error, life table and survival analysis.
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Abstract: Peter Congdon's Bayesian Statistical Modelling is not a teaching textbook or introduction to Bayesian statistical modelling. Although the basics of Bayesian theory and Markov Chain Monte Carlo (MCMC) methods are briefly reviewed in the book, I think that one should already be familiar with those topics before using the book. Given that, the book can be very helpful to an applied statistician, as it is an excellent reference source for Bayesian models and literature. Using nearly 200 worked examples with data examples and computer code available via the World Wide Web, the book reviews a large number of models, e.g., for standard distributions, classification, regression, hierarchical pooling of information, missing data, correlated data, multivariate data, time series, spatial data, longitudinal data, measurement error, life table and survival analysis. Each chapter starts with an introduction to the model family and then continues with describing variations to basic models, with advice as to model identification, prior selection, interpretation of findings, and computing choices and strategies. In the last chapter also the Bayesian model assessment is briefly reviewed. With 500 pages in the book, there are about 2.5 pages per example, and consequently I believe that in most cases it would be necessary to read also some of the references in order to fully benefit from the models described. Although the data examples are mainly from medical science, public health and the social sciences, the book should be interesting to any applied statistician seeking new possibilities in data analysis. Aki Vehtari
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References
Supergauge Transformations in Four-Dimensions
Julius Wess,Bruno Zumino +1 more
TL;DR: In this article, supergauge transformations are defined in four space-time dimensions and their commutators are shown to generate γ5 transformations and conformal transformations, respectively.
2.9K
Is the Neutrino a Goldstone Particle
D.V. Volkov,V.P. Akulov +1 more
TL;DR: In this paper, a phenomenological Lagrangian is constructed to describe an interaction of the neutrino with itself and with other particles, based on the hypothesis that neutrinos are goldstone particles.
1.7K
All Possible Symmetries of the S Matrix
TL;DR: In this article, a new theorem on the impossibility of combining space-time and internal symmetries in any but a trivial way was proved, which is applicable to infinite-parameter groups, instead of just to Lie groups.
1.3K
•Book
Supersymmetric Methods in Quantum and Statistical Physics
Georg Junker
- 30 Sep 1996
TL;DR: In this article, the Witten model was used to solve the exact solution of quantum-mechanical Eigenvalue problems in classical stochastic dynamics and supersymmetry in the Pauli and Dirac Equations.
724
Über das Wasserstoffspektrum vom Standpunkt der neuen Quantenmechanik
TL;DR: In this paper, the Balmerterme eines Atoms with einem einzigen Elektron aus der neuen Quantenmechanik richtig ergeben and das die in der bisherigen Theorie aus den Zusatzverboten von singularen Bewegungen entstehenden Schwierigkeiten, die insbesondere im Falle der gekreuzten Felder zutage treten, in der neueen Theorie verschwinden.
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