Bayesian statistics and new generations : BAYSM 2018, Warwick, UK, July 2-3, selected contributions
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Bibliographic Information
Bayesian statistics and new generations : BAYSM 2018, Warwick, UK, July 2-3, selected contributions
（Springer proceedings in mathematics & statistics, v. 296）
Springer, c2019
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Includes bibliographical references and index
Description and Table of Contents
Description
This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018. The meeting provided a valuable opportunity for young researchers, MSc students, PhD students, and postdocs interested in Bayesian statistics to connect with the broader Bayesian community. The proceedings offer cutting-edge papers on a wide range of topics in Bayesian statistics, identify important challenges and investigate promising methodological approaches, while also assessing current methods and stimulating applications. The book is intended for a broad audience of statisticians, and demonstrates how theoretical, methodological, and computational aspects are often combined in the Bayesian framework to successfully tackle complex problems.
Table of Contents
Part I - Theory and Methods: A. Diana, J. Griffin, and E. Matechou, A Polya Tree Based Model for Unmarked Individuals in an Open Wildlife Population.- S. Haque and K. Mengersen, Bias Estimation and Correction Using Bootstrap Simulation of the Linking Process.- N. Laitonjam and N. Hurley, Non-parametric Overlapping Community Detection.- L. Fee Schneider, T. Staudt, and A. Munk, Posterior Consistency in the Binomial Model with Unknown Parameters: A Numerical Study.- C. Spire and D. Chakrabarty, Learning in the Absence of Training Data - a Galactic Application.- D. Tait and B. Worton, Multiplicative Latent Force Models.- PART II - Computational Statistics: N. Cunningham, J. E. Griffin, D. L. Wild, and A. Lee, particleMDI: A Julia Package for the Integrative Cluster Analysis of Multiple Datasets.- D. Hosszejni and G. Kastner, Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage.- B. Karimi and M. Lavielle, Efficient Metropolis-Hastings Sampling for Nonlinear Mixed Effects Models.- G. Kratzer, Reinhard Furrer, and Pittavino Marta. Comparison Between Suitable Priors for Additive Bayesian Networks.- I. Peneva and R. Savage, A Bayesian Nonparametric Model for Integrative Clustering of Omics Data.- I. Schwabe, Bayesian Inference of Interaction Effects in Item-Level Hierarchical Twin Data.- PART III - Applied Statistics: K. Brock, L. Billingham, C. Yap, and G. Middleton, A Phase II Clinical Trial Design for Associated Co-Primary Efficacy and Toxicity Outcomes with Baseline Covariates.- E. Lanzarone, E. Scalco, A. Mastropietro, S. Marzi, and G. Rizzo, A Conditional Autoregressive Model for estimating Slow and Fast Diffusion from Magnetic Resonance Images.- D. Rocha, M. Scotto, C. Pinto, J. Nuno Tavares, and S. Gouveia, Simulation Study of HIV Temporal Patterns Using Bayesian Methodology.- A. Shenvi, J. Smith, R. Walton, and S. Eldridge, Modelling with Non-Stratified Chain Event Graphs.- O. Stevenson and B. Brewer, Modelling Career Trajectories of Cricket Players Using Gaussian Processes.- F. Turner, R. Wilkinson, C. Buck, J. Jones, and L. Sime, Ice Cores and Emulation: Learning More About Past Ice Sheet Shapes.
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