Physical description 
1 online resource (ix, 251 pages) : illustrations (some color). 
Series 
Springer proceedings in mathematics & statistics, 21941009 ; volume 194


Springer proceedings in mathematics & statistics ; v. 194.


Springer Mathematics and Statistics eBooks 2017 English+International

Contents 
Preface; Contents; Part I Theory and Methods; Sequential Monte Carlo Methods in Random Intercept Models for Longitudinal Data; 1 Introduction; 2 Bayesian Random Intercept Model; 3 Sequential Monte Carlo Methods; 4 Application; 5 Conclusions; References; On the Truncation Error of a Superposed Gamma Process; 1 Introduction; 2 Sampling Completely Random Measures; 2.1 Completely Random Measures; 2.2 Ferguson and Klass Algorithm; 3 Truncation Error of the Superposed Gamma Process; 3.1 Bound in Probability; 3.2 MomentMatching Criterion; References. 

On the Study of Two Models for IntegerValued HighFrequency Data1 Introduction; 2 Distributions for Tick Data; 2.1 Skellam Distribution; 2.2 Folded Geometric Distribution; 3 Algorithms; 4 Application; 5 Discussion; References; Identification and Estimation of Principal Causal Effects in Randomized Experiments with Treatment Switching; 1 Introduction; 2 Principal Stratification Approach to Treatment Switching; 3 Identification Assumptions; 4 Partially Simulated Case Study; 4.1 Estimation Strategy; 4.2 Results and Comments; References; A Bayesian Joint Dispersion Model with Flexible Links. 

1 Introduction2 Model Specification; 2.1 Longitudinal Mixed Dispersion Model; 2.2 Hazard Model with TimeVarying Coefficients; 3 The Posterior Distribution; 4 HIV/AIDS Data Analysis; 4.1 Fitted Models; 4.2 Results; 5 Discussion; References; Local Posterior Concentration Rate for Multilevel Sparse Sequences; 1 Introduction; 2 Preliminaries; 2.1 Notation; 2.2 Empirical Bayes Posterior; 3 Main Results; References; Likelihood Tempering in Dynamic Model Averaging; 1 Introduction; 2 OnLine Prediction with a Set of Admissible Models; 2.1 Dynamic Model Averaging; 3 Tempered Bayesian Update. 

4 MixtureBased Approach5 Simulation Results; 6 Conclusion; References; Localization in HighDimensional Monte Carlo Filtering; 1 Introduction; 2 Ensemble Filtering Algorithms; 3 Local Algorithms; 4 Simulation Studies; 4.1 Conjugate Normal Setup; 4.2 Filtering with the Lorenz96 Model; 5 Conclusion; References; Linear Inverse Problem with Range Prior on Correlations and Its Variational Bayes Inference; 1 Introduction; 2 Mathematical Method; 2.1 Bayesian Hierarchical Model; 3 Experiments; 3.1 Toy Example; 3.2 Realistic Example; 4 Conclusion; References; Part II Applications and Case Studies. 

Bayesian Hierarchical Model for Assessment of Climate Model Biases1 Introduction; 2 Bayesian Hierarchical Approach for Climate Model Biases; 3 Application to Temperature Bias in the Tropical Atlantic Region; 3.1 Choice of Weighting Functions; 3.2 Results; 4 Conclusions; References; An Application of Bayesian Seemingly Unrelated Regression Models with Flexible Tails; 1 Introduction; 2 Bayesian SUR Model with Modt Distribution; 2.1 Modt Distribution; 2.2 SUR Model; 2.3 MCMC Algorithm; 3 Application; 3.1 Capital Asset Pricing Model (CAPM); 3.2 Results; 4 Conclusion; References. 
Summary 
This book is a selection of peerreviewed contributions presented at the third Bayesian Young Statisticians Meeting, BAYSM 2016, Florence, Italy, June 1921. The meeting provided a unique opportunity for young researchers, M.S. students, Ph. D. students, and postdocs dealing with Bayesian statistics to connect with the Bayesian community at large, to exchange ideas, and to network with others working in the same field. The contributions develop and apply Bayesian methods in a variety of fields, ranging from the traditional (e.g., biostatistics and reliability) to the most innovative ones (e.g., big data and networks). 
Other author 
Argiento, Raffaele, editor.


Lanzarone, Ettore, editor.


Villalobos, Isadora Antoniano, editor.


Mattei, Alessandra, editor.


SpringerLink issuing body.

Subject 
Bayesian statistical decision theory  Congresses.


Neural networks (Computer science)  Congresses.


Electronic books. 

Conference papers and proceedings. 
Variant Title 
BAYSM 2016 
ISBN 
9783319540849 (electronic bk.) 

331954084X (electronic bk.) 

9783319540832 (print) 

3319540831 
Standard Number 
10.1007/9783319540849 
