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

Contributor(s):

Material type: Text

text

Media type:

computer

Carrier type:

online resource

ISBN:

9780191647000
9780199695607

Subject(s):

Bayesian statistical decision theory

Genre/Form:

Electronic Books.

LOC classification:

QA279 .B394 2013

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Contents:

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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Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD)	G. Allen Fleece Library ONLINE	Non-fiction	QA279.5 (Browse shelf(Opens below))	Link to resource	Available		ocn826443506

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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.

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 statisticsâ€?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 Smithâ€?s research supervision (PhD)""; ""Adrian Smithâ€?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""

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