| Description |
1 online resource (xi, 702 pages) : illustrations |
| Contents |
""Cover""; ""Contents""; ""Contributors""; ""Introduction""; ""Part I: Exchangeability""; ""1 Observables and models: exchangeability and the inductive argument""; ""2 Exchangeability and its ramifications""; ""Part II: Hierarchical Models""; ""3 Hierarchical modelling""; ""4 Bayesian hierarchical kernel machines for nonlinear regression and classification""; ""5 Flexible Bayesian modelling for clustered categorical responses in developmental toxicology""; ""Part III: Markov Chain Monte Carlo""; ""6 Markov chain Monte Carlo methods""; ""7 Advances in Markov chain Monte Carlo"" |
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""Part IV: Dynamic Models""""8 Bayesian dynamic modelling""; ""9 Hierarchical modelling in time series: the factor analytic approach""; ""10 Dynamic and spatial modelling of block maxima extremes""; ""Part V: Sequential Monte Carlo""; ""11 Online Bayesian learning in dynamic models: an illustrative introduction to particle methods""; ""12 Semi-supervised classification of texts using particle learning for probabilistic automata""; ""Part VI: Nonparametrics""; ""13 Bayesian nonparametrics""; ""14 Geometric weight priors and their applications"" |
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""15 Revisiting Bayesian curve fitting using multivariate normal mixtures""""Part VII: Spline Models and Copulas""; ""16 Applications of Bayesian smoothing splines""; ""17 Bayesian approaches to copula modelling""; ""Part VIII: Model Elaboration and Prior Distributions""; ""18 Hypothesis testing and model uncertainty""; ""19 Proper and non-informative conjugate priors for exponential family models""; ""20 Bayesian model specification: heuristics and examples""; ""21 Case studies in Bayesian screening for time-varying model structure: the partition problem"" |
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""Part IX: Regressions and Model Averaging""""22 Bayesian regression structure discovery""; ""23 Gibbs sampling for ordinary, robust and logistic regression with Laplace priors""; ""24 Bayesian model averaging in the M-open framework""; ""Part X: Finance and Actuarial Science""; ""25 Asset allocation in finance: a Bayesian perspective""; ""26 Markov chain Monte Carlo methods in corporate finance""; ""27 Actuarial credibility theory and Bayesian statistics�the story of a special evolution""; ""Part XI: Medicine and Biostatistics""; ""28 Bayesian models in biostatistics and medicine"" |
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""29 Subgroup analysis""""30 Surviving fully Bayesian nonparametric regression models""; ""Part XII: Inverse Problems and Applications""; ""31 Inverse problems""; ""32 Approximate marginalization over modelling errors and uncertainties in inverse problems""; ""33 Bayesian reconstruction of particle beam phase space""; ""Adrian Smith�s research supervision (PhD)""; ""Adrian Smith�s publications""; ""Index""; ""A""; ""B""; ""C""; ""D""; ""E""; ""F""; ""G""; ""H""; ""I""; ""J""; ""K""; ""L""; ""M""; ""N""; ""O""; ""P""; ""Q""; ""R""; ""S""; ""T""; ""U""; ""V""; ""W""; ""Z"" |
| Summary |
This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field |
| Bibliography |
Includes bibliographical references |
| Notes |
Print version record |
| Subject |
Bayesian statistical decision theory.
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MATHEMATICS -- Probability & Statistics -- Bayesian Analysis.
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Bayesian statistical decision theory
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| Form |
Electronic book
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| Author |
Damien, Paul, 1960- editor.
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Dellaportas, Petros, editor
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Polson, Nicholas G., 1963- editor.
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Stephens, David A., editor
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| ISBN |
9780191647000 |
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0191647004 |
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9780199695607 |
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0199695601 |
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