Bayesian Statistics in Action

1. Front Matter

   Pages i-ix

   PDF

2. Theory and Methods

   1. Front Matter

      Pages 1-1

      PDF

   2. Sequential Monte Carlo Methods in Random Intercept Models for Longitudinal Data

      • Danilo Alvares, Carmen Armero, Anabel Forte, Nicolas Chopin

      Pages 3-9

   3. On the Truncation Error of a Superposed Gamma Process

      • Julyan Arbel, Igor Prünster

      Pages 11-19

   4. On the Study of Two Models for Integer-Valued High-Frequency Data

      • Andrea Cremaschi, Jim E. Griffin

      Pages 21-30

   5. Identification and Estimation of Principal Causal Effects in Randomized Experiments with Treatment Switching

      • Emanuele Gramuglia

      Pages 31-37

   6. A Bayesian Joint Dispersion Model with Flexible Links

      • Rui Martins

      Pages 39-49

   7. Local Posterior Concentration Rate for Multilevel Sparse Sequences

      • Eduard Belitser, Nurzhan Nurushev

      Pages 51-66

   8. Likelihood Tempering in Dynamic Model Averaging

      • Jan Reichl, Kamil Dedecius

      Pages 67-77

   9. Localization in High-Dimensional Monte Carlo Filtering

      • Sylvain Robert, Hans R. Künsch

      Pages 79-89

   10. Linear Inverse Problem with Range Prior on Correlations and Its Variational Bayes Inference

       • Ondřej Tichý, Václav Šmídl

       Pages 91-101

3. Applications and Case Studies

   1. Front Matter

      Pages 103-103

      PDF

   2. Bayesian Hierarchical Model for Assessment of Climate Model Biases

      • Maeregu Woldeyes Arisido, Carlo Gaetan, Davide Zanchettin, Angelo Rubino

      Pages 105-113

   3. An Application of Bayesian Seemingly Unrelated Regression Models with Flexible Tails

      • Charles Au, S. T. Boris Choy

      Pages 115-125

   4. Bayesian Inference of Stochastic Pursuit Models from Basketball Tracking Data

      • Harish S. Bhat, R. W. M. A. Madushani, Shagun Rawat

      Pages 127-137

   5. Identification of Patient-Specific Parameters in a Kinetic Model of Fluid and Mass Transfer During Dialysis

      • Camilla Bianchi, Ettore Lanzarone, Giustina Casagrande, Maria Laura Costantino

      Pages 139-149

   6. A Bayesian Nonparametric Approach to Ecological Risk Assessment

      • Guillaume Kon Kam King, Julyan Arbel, Igor Prünster

      Pages 151-159

   7. Approximate Bayesian Computation Methods in the Identification of Atmospheric Contamination Sources for DAPPLE Experiment

      • Piotr Kopka, Anna Wawrzynczak, Mieczyslaw Borysiewicz

      Pages 161-171

   8. Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases

      • Elena Lázaro, Carmen Armero, Luis Rubio

      Pages 173-181

   9. Randomization Inference and Bayesian Inference in Regression Discontinuity Designs: An Application to Italian University Grants

      • Federica Licari

      Pages 183-191

This book is a selection of peer-reviewed contributions presented at the third Bayesian Young Statisticians Meeting, BAYSM 2016, Florence, Italy, June 19-21. 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).

• Bayesan statistics
• Theoretical and Applied statistics
• Computational statistics
• Young researchers
• Statistical tehory and methods

• CNR–IMATI, Milano, Italy

  Raffaele Argiento

• CNR-IMATI, Milan, Italy

  Ettore Lanzarone

• Decision Sciences, Bocconi University, Milan, Italy

  Isadora Antoniano Villalobos

• Dipartimento di Statistica "G. Parenti", Università di Firenze, Firenze, Italy

  Alessandra Mattei

​Raffaele Argiento is an assistant professor of statistics at the Department of Economic, Social, Mathematical and Statistical Sciences (ESOMAS) of the University of Turin, Italy. He obtained an M.Sc. degree in mathematics from Federico II University, Naples, Italy, in 2000 and a Ph.D. in statistics from Bocconi University, Milan, Italy, in 2007. He is affiliated to the "de Castro" Statistics initiative of the Collegio Carlo Alberto, Turin, Italy. He is a member of the board for the Ph.D. in statistics at Bocconi University. His research focuses on Bayesian parametric and nonparametric methods from both theoretical and applied viewpoints. He is the executive director of the Applied Bayesian Summer School (ABS) and a member of the BAYSM board.

Ettore Lanzarone is a researcher at the Institute of Applied Mathematics and Information Technology ``E. Magenes'' (IMATI) at the National Research Council of Italy (CNR) in Milan, Italy. He obtained an M.Sc. degree in biomedicalengineering and a Ph.D. in bioengineering from Politecnico di Milano, Italy, in 2004 and 2008, respectively. He is adjunct professor at the Department of Mathematics of Politecnico di Milano, Milan, Italy, and a collaborating member of the CIRRELT laboratory, Montréal and Quebec City, Canada. His research interests include prediction methods (Bayesian in particular), optimization and operations research, and bioengineering. He is cofounder of the BAYSM conferences and a member of the BAYSM board.

Isadora Antoniano-Villalobos is an assistant professor of statistics at the Department of Decision Sciences and a member of the board for the Ph.D. in statistics at Bocconi University, Milan, Italy. She obtained an M.Sc. degree in mathematics from the Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico, in 2008 and a Ph.D. in statistics from the University of Kent, Canterbury, UK, in 2013. Her research focuses on nonparametric Bayesian models and methods, sensitivity analysis, and extreme value theory. She was chair-elect and chair of the junior section of the International Society for Bayesian Analysis (j-ISBA) in 2014 and 2015-2016.

Alessandra Mattei is an assistant professor of statistics at the Department of Statistics, Computer Science, Applications ``G. Parenti'' at the University of Florence, Italy, where she also obtained her M.A. in statistics and Ph.D. in applied statistics. In 2012 she was a research fellow at the Statistical and Applied Mathematical Sciences Institute (SAMSI), NC, USA. She has given short courses in Causal Inference. She is currently associate editor for the Journal of the Royal Statistical Society A. Her research interests include causal inference in experimental and observational studies, Bayesian inference, and inference with missing data problems.

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