The Contribution of Young Researchers to Bayesian Statistics

Part 1 Theoretical Bayes.- Chapter 1 A nonparametric model for stationary time series.- Chapter 2 Estimation of optimally combine-biomarker accuracy in the absence of a gold standard reference test.- Chapter 3 On Bayesian transformation selection: problem formulation and preliminary results.- Chapter 4 A simple proof for the multinomial version of representation theorem.- Chapter 5 A sequential Monte Carlo framework for adaptive Bayesian model discrimination designs using mutual information.- Chapter 6 Joint parameter estimation and biomass tracking in a stochastic predator-prey system.- Chapter 7 Adaptive Bayes test for monotonicity.- Chapter 8 Bayesian inference on individual-based models by controlling the random inputs.- Chapter 9 Consistency of Bayesian nonparametric hidden Markov models.- Chapter 10 Bayesian methodology in the stochastic event reconstruction problems.- Part 2 Computational Bayes.- Chapter 11 Efficient fitting of Bayesian regression models with spatio-temporally varying coefficients.- Chapter 12 Scalable automation of Monte Carlo methods.- Chapter 13 Approximate Bayesian computation for the elimination of nuisance parameters.- Chapter 14 Reweighting schemes based on particle methods.- Chapter 15 Bayesian inference of money flows due to international travelers on planned and unplanned domains.- Chapter 16 Parallel slice sampling.- Chapter 17 Approximate Bayesian computation (ABC) in quantile regression.- Part 3 Bayes @ work: appraisal of applications to the real world.- Chapter 18 Spatio-temporal model for short-term predictions of air pollution data.- Chapter 19 Predicting rainfall fields from lightnings records: a hierarchical Bayesian approach.- Chapter 20 An approach to environmental problem based on PFLOTRAN package.- Chapter 21 Bayesian hierarchical modeling of growth via Gompertz model: an application in poultry.- Chapter 22 Bayesian prediction of SMART power semiconductor lifetime with Bayesian networks.- Chapter 23 Consumer-oriented

Ettore Lanzarone is a Permanent Researcher at the division of Milan of the Institute of Applied Mathematics and Information Technology (IMATI) of the National Research Council of Italy (CNR), Milan, Italy. He is also Adjunct Professor Mathematical Analysis at the Politecnico di Milano, Milan, Italy. He obtained his Ph.D. in Bioengineering in June 2008 at the Politecnico di Milano, and his master degree in Biomedical Engineering cum laude in April 2004 at the Politecnico di Milano. He is member of the European Working Group on Operational Research Applied to Health Services (ORAHS) and of the Italian National Bioengineering Group (GNB).  His current research interests include: parameter estimation and stochastic evolution of dynamic systems described by ordinary and partial differential equations; stochastic models for estimating the demand and planning the activities in healthcare structures; modelling and in-vitro studies of the cardiovascular fluid dynamics.

Francesca Ieva is a Postdoctoral Research Fellow at the Modeling and Scientific Computing Lab (MOX), Department of Mathematics, Politecnico di Milano, Milan, Italy. She obtained her Ph.D. in Mathematical Models and Methods for Engineering and her master degree in Mathematical Engineering at the Politecnico di Milano in 2012 and 2008, respectively. She is member of ISBA (and Program Chair of the junior section), RSS, SIS (and Chair of the young section) and SIAM. Her research activities include Statistical Learning in Biomedical context, focused on modelling data arising from integration of clinical surveys and administrative databanks, Clinical Biostatistics, Healthcare assessment, Mixed Effects Models and Semi-parametric Bayesian hierarchical models, Depth Measures and Multivariate Functional Data Analysis for applications to ECG signals, Multi State Models for the analysis of chronic diseases progression like heart failures.