The Contribution of Young Researchers to Bayesian Statistics

The first Bayesian Young Statisticians Meeting, BAYSM 2013, has provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and post-docs dealing with Bayesian statistics to connect with the Bayesian community at large, exchange ideas, and network with scholars working in their field. The Workshop, which took place June 5th and 6th 2013 at CNR-IMATI, Milan, has promoted further research in all the fields where Bayesian statistics may be employed under the guidance of renowned plenary lecturers and senior discussants. A selection of the contributions to the meeting and the summary of one of the plenary lectures compose this volume.

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 new-product development in fruit flavour breeding-a Bayesian approach.- Chapter 24 Bayesian layer-counting in ice-cores-reconstructing the time scale.- Part 4 A Bayesian approach to bio-statistics and health sciences.- Chapter 25 Bayesian analysis and prediction of patients' demands for visits in home care.- Chapter 26 Exploiting adaptive Bayesian regression shrinkage to identify exome sequence variants associated with gene expression.- Chapter 27 Randomized phase II trials: a Bayesian two-stage design.- Chapter 28 Bayesian matrix factorization for outlier detection: an application in population genetics.- Chapter 29 Noise model selection for multichannel diffusion-weighted MRI.- Chapter 30 Analysis of hospitalizations of patients affected by chronic heart disease.- Chapter 31 A semiparametric Bayesian multivariate model for survival probabilities after acute myocardial infarction.- Chapter 32 Particle learning approach to Bayesian model selection: an application from neurology.- Part 5 Bayesian models for stochastic and economic processes.- Chapter 33 Locally adaptive Bayesian covariance regression.- Chapter 34 Locally adaptive Bayesian covariance regression.- Chapter 35 Efficient Bayesian inference for multivariate factor stochastic volatility models.- Chapter 36 Poisson driven stationary Markovian models.- Chapter 37 Claim sizes in the compound Poisson process from a Bayesian viewpoint.- Chapter 38 Land rental market and agricultural production efficiency: a Bayesian perspective.- Part 6 Suggestions for young readers.- Chapter 39 The point is...to publish?.