New Frontiers in Bayesian Statistics : BAYSM 2021, Online, September 1-3

1 Andrej Srakar, Approximate Bayesian algorithm for tensor robust principal component analysis.- 2 Yuanqi Chu, Xueping Hu, Keming Yu, Bayesian Quantile Regression for Big Data Analysis.- 3 Peter Strong, Alys McAlphine, Jim Smith, Towards A Bayesian Analysis of Migration Pathways using Chain Event Graphs of Agent Based Models.- 4 Giorgos Tzoumerkas, Dimitris Fouskakis, Power-Expected-Posterior Methodology with Baseline Shrinkage Priors.- 5 Mica Teo, Sara Wade, Bayesian nonparametric scalar-on-image regression via Potts-Gibbs random partition models.- 6 Alessandro Colombi, Block Structured Graph Priors in Gaussian Graphical Models.- 7 Jessica Pavani, Paula Moraga, A Bayesian joint spatio-temporal model for multiple mosquito-borne diseases.- 8 Ivan Gutierrez, Luis Gutierrez, Danilo Alvare, A Bayesian nonparametric test for cross-group differences relative to a control.- 9 Francesco Gaffi, Antonio Lijoi, Igor Pruenster, Specification of the base measure of nonparametric priors via random means.- 10 Matteo Pedone, Raffaele Argiento, Francesco Claudio Stingo, Bayesian Nonparametric Predictive Modeling for Personalized Treatment Selection.- 11 Gabriel Calvo, carmen armero, Virgilio Gomez-Rubio, Guido Mazzinari, Bayesian growth curve model for studying the intra-abdominal volume during pneumoperitoneum for laparoscopic surgery.