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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 Moment-Matching Criterion; References
On the Study of Two Models for Integer-Valued High-Frequency 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 Time-Varying 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 On-Line Prediction with a Set of Admissible Models; 2.1 Dynamic Model Averaging; 3 Tempered Bayesian Update
4 Mixture-Based Approach5 Simulation Results; 6 Conclusion; References; Localization in High-Dimensional 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 Mod-t Distribution; 2.1 Mod-t Distribution; 2.2 SUR Model; 2.3 MCMC Algorithm; 3 Application; 3.1 Capital Asset Pricing Model (CAPM); 3.2 Results; 4 Conclusion; References
On the Study of Two Models for Integer-Valued High-Frequency 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 Time-Varying 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 On-Line Prediction with a Set of Admissible Models; 2.1 Dynamic Model Averaging; 3 Tempered Bayesian Update
4 Mixture-Based Approach5 Simulation Results; 6 Conclusion; References; Localization in High-Dimensional 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 Mod-t Distribution; 2.1 Mod-t Distribution; 2.2 SUR Model; 2.3 MCMC Algorithm; 3 Application; 3.1 Capital Asset Pricing Model (CAPM); 3.2 Results; 4 Conclusion; References