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Bayesian theory and applications / edited by Paul Damien, Petros Dellaportas, Nicholas G. Polson, & David A. Stephens.

Contributor(s): Material type: TextTextPublication details: Oxford : Oxford University Press, 2013.Description: 1 online resource (xi, 702 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780191647000
  • 0191647004
  • 9780199695607
  • 0199695601
Subject(s): Genre/Form: Additional physical formats: Print version:: Bayesian theory and applications.DDC classification:
  • 519.5/42 23
LOC classification:
  • QA279.5
Online resources:
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""
""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""
""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""
""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""
""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.
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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.

Print version record.

Includes bibliographical references.

""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""

""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""

""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""

""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""

""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""

Master record variable field(s) change: 650

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