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Bayesian statistics from methods to models and applications[electronic resource] :research from BAYSM 2014 /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	519.542
書名/作者:	Bayesian statistics from methods to models and applications : research from BAYSM 2014 // edited by Sylvia Fruhwirth-Schnatter ... [et al.].
其他作者:	Fruhwirth-Schnatter, Sylvia.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	xiii, 167 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Bayesian statistical decision theory - Congresses.
標題:	Neural networks (Computer science)
標題:	Statistics.
標題:	Statistical Theory and Methods.
標題:	Statistics for Business/Economics/Mathematical Finance/Insurance.
標題:	Statistics and Computing/Statistics Programs.
ISBN:	9783319162386 (electronic bk.)
ISBN:	9783319162379 (paper)
內容註:	On Bayesian based adaptive confidence sets for linear functionals -- A new finite approximation for the NGG mixture model: an application to density estimation -- Distributed Estimation of Mixture Models -- Bayesian Survival Model based on Moment Characterization -- Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Predictive Check -- A subordinated stochastic process model -- Jeffreys priors for mixture estimation -- Bayesian Variable Selection for Generalized Linear Models Using the Power-Conditional-Expected-Posterior Prior -- A new strategy for testing cosmology with simulations -- Mixture Model for Filtering Firms' Profit Rates -- Bayesian Estimation of the Aortic Stiffness based on Non-Invasive Computed Tomography Images -- Formal and Heuristic Model Averaging Methods for Predicting the US Unemployment Rate -- Bayesian Filtering for Thermal Conductivity Estimation given Temperature Observations -- Application of Interweaving in DLMs to an Exchange and Specialization Experiment.
摘要、提要註:	The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Universite Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session with 30 contributions. Selected contributions have been drawn from the conference for this book. All contributions in this volume are peer-reviewed and share original research in Bayesian computation, application, and theory.
電子資源:	http://dx.doi.org/10.1007/978-3-319-16238-6

Bayesian statistics from methods to models and applications[electronic resource] :research from BAYSM 2014 /
Bayesian statistics from methods to models and applicationsresearch from BAYSM 2014 /[electronic resource] :edited by Sylvia Fruhwirth-Schnatter ... [et al.]. - Cham :Springer International Publishing :2015. - xiii, 167 p. :ill., digital ;24 cm. - Springer proceedings in mathematics & statistics,v.1262194-1009 ;. - Springer proceedings in mathematics & statistics ;v.70..

On Bayesian based adaptive confidence sets for linear functionals -- A new finite approximation for the NGG mixture model: an application to density estimation -- Distributed Estimation of Mixture Models -- Bayesian Survival Model based on Moment Characterization -- Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Predictive Check -- A subordinated stochastic process model -- Jeffreys priors for mixture estimation -- Bayesian Variable Selection for Generalized Linear Models Using the Power-Conditional-Expected-Posterior Prior -- A new strategy for testing cosmology with simulations -- Mixture Model for Filtering Firms' Profit Rates -- Bayesian Estimation of the Aortic Stiffness based on Non-Invasive Computed Tomography Images -- Formal and Heuristic Model Averaging Methods for Predicting the US Unemployment Rate -- Bayesian Filtering for Thermal Conductivity Estimation given Temperature Observations -- Application of Interweaving in DLMs to an Exchange and Specialization Experiment.

The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Universite Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session with 30 contributions. Selected contributions have been drawn from the conference for this book. All contributions in this volume are peer-reviewed and share original research in Bayesian computation, application, and theory.

ISBN: 9783319162386 (electronic bk.)

Standard No.: 10.1007/978-3-319-16238-6doiSubjects--Topical Terms:

484403
Bayesian statistical decision theory
--Congresses.

LC Class. No.: QA279.5

Dewey Class. No.: 519.542

Bayesian statistics from methods to models and applications[electronic resource] :research from BAYSM 2014 /
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