LEADER 03842nam 22006375 450 001 9910768195003321 005 20250602120638.0 010 $a9783031424137 010 $a3031424131 024 7 $a10.1007/978-3-031-42413-7 035 $a(MiAaPQ)EBC30979441 035 $a(Au-PeEL)EBL30979441 035 $a(CKB)29127000000041 035 $a(OCoLC)1414468451 035 $a(DE-He213)978-3-031-42413-7 035 $a(EXLCZ)9929127000000041 100 $a20231129d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBayesian Statistics, New Generations New Approaches $eBAYSM 2022, Montréal, Canada, June 22?23 /$fedited by Alejandra Avalos-Pacheco, Roberta De Vito, Florian Maire 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (119 pages) 225 1 $aSpringer Proceedings in Mathematics & Statistics,$x2194-1017 ;$v435 311 08$aPrint version: Avalos-Pacheco, Alejandra Bayesian Statistics, New Generations New Approaches Cham : Springer International Publishing AG,c2024 9783031424120 327 $aJ. Owen, I. Vernon, J. Carter, Bayesian Emulation of Complex Computer Models with Structured Partial Discontinuities -- B. Hansen, A. Avalos-Pacheco, M. Russo, Roberta De Vito, A Variational Bayes Approach to Factor Analysis. P. Strong, Jim Q. Smith, Scalable Model Selection for Staged Trees: Mean-posterior Clustering and Binary Trees -- G. Vasdekis, Gareth O. Roberts, Speeding up the Zig-Zag process -- V. Ghidini, S. Legramanti, R. Argiento, Extended Stochastic Block Model with Spatial Covariates for Weighted Brain Networks -- A. Lachi, C. Viscardi, M. Baccini, Approximate Bayesian inference for smoking habit dynamics in Tuscany. 330 $aThis book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montréal, Canada, held on June 22?23, titled "Bayesian Statistics, New Generations New Approaches". This collection features selected peer-reviewed contributions that showcase the vibrant and diverse research presented at meeting. This book is intended for a broad audience interested in statistics and aims at providing stimulating contributions to theoretical, methodological, and computational aspects of Bayesian statistics. The contributions highlight various topics in Bayesian statistics, presenting promising methodological approaches to address critical challenges across diverse applications. This compilation stands as a testament to the talent and potential within the j-ISBA community. This book is meant to serve as a catalyst for continued advancements in Bayesian methodology and its applications and encourages fruitful collaborations that push the boundaries ofstatistical research. 410 0$aSpringer Proceedings in Mathematics & Statistics,$x2194-1017 ;$v435 606 $aStatistics 606 $aStatistics 606 $aStatistical Theory and Methods 606 $aBayesian Network 606 $aBayesian Inference 606 $aEstadística bayesiana$2thub 608 $aCongressos$2thub 608 $aLlibres electrònics$2thub 615 0$aStatistics. 615 0$aStatistics. 615 14$aStatistical Theory and Methods. 615 24$aBayesian Network. 615 24$aBayesian Inference. 615 7$aEstadística bayesiana 676 $a519.542 700 $aAvalos-Pacheco$b Alejandra$01453488 701 $aDe Vito$b Roberta$01453489 701 $aMaire$b Florian$01453490 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910768195003321 996 $aBayesian Statistics, New Generations New Approaches$93656135 997 $aUNINA