找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Bayesian Statistics, New Generations New Approaches; BAYSM 2022, Montréal Alejandra Avalos-Pacheco,Roberta De Vito,Florian M Conference pro

[復制鏈接]
查看: 49067|回復: 45
樓主
發(fā)表于 2025-3-21 17:53:16 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Bayesian Statistics, New Generations New Approaches
期刊簡稱BAYSM 2022, Montréal
影響因子2023Alejandra Avalos-Pacheco,Roberta De Vito,Florian M
視頻videohttp://file.papertrans.cn/182/181886/181886.mp4
發(fā)行地址Provides recent advanced techniques in Bayesian analysis.Focus on contributions with novel Bayesian approaches that tackle a problem of key importance.Produces a wide range of approaches for Bayesian
學科分類Springer Proceedings in Mathematics & Statistics
圖書封面Titlebook: Bayesian Statistics, New Generations New Approaches; BAYSM 2022, Montréal Alejandra Avalos-Pacheco,Roberta De Vito,Florian M Conference pro
影響因子.This 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..
Pindex Conference proceedings 2023
The information of publication is updating

書目名稱Bayesian Statistics, New Generations New Approaches影響因子(影響力)




書目名稱Bayesian Statistics, New Generations New Approaches影響因子(影響力)學科排名




書目名稱Bayesian Statistics, New Generations New Approaches網絡公開度




書目名稱Bayesian Statistics, New Generations New Approaches網絡公開度學科排名




書目名稱Bayesian Statistics, New Generations New Approaches被引頻次




書目名稱Bayesian Statistics, New Generations New Approaches被引頻次學科排名




書目名稱Bayesian Statistics, New Generations New Approaches年度引用




書目名稱Bayesian Statistics, New Generations New Approaches年度引用學科排名




書目名稱Bayesian Statistics, New Generations New Approaches讀者反饋




書目名稱Bayesian Statistics, New Generations New Approaches讀者反饋學科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權限
沙發(fā)
發(fā)表于 2025-3-21 20:38:45 | 只看該作者
Caryn Hoang,James D. Miles,Kim-Phuong L. Vued by the mean posterior distributions, we can outperform existing methods in computational time whilst providing comparable model scores. This method also enables us to learn more complex relationships than existing model selection techniques by expanding the model space. We illustrate how this can embellish inferences in a real study.
板凳
發(fā)表于 2025-3-22 02:51:27 | 只看該作者
Zitao Cheng,Keiko Kasamatsu,Takeo Ainoya Bayesian Computation, a powerful simulation-based inference method, to provide posterior estimates of the model’s parameters. Using these approximate posterior distributions, we predicted the prevalence of current, former, and never smokers in Tuscany up to 2043. The model results suggest that the prevalence of smokers will decrease over time.
地板
發(fā)表于 2025-3-22 07:47:27 | 只看該作者
5#
發(fā)表于 2025-3-22 12:29:58 | 只看該作者
6#
發(fā)表于 2025-3-22 13:36:06 | 只看該作者
7#
發(fā)表于 2025-3-22 18:57:29 | 只看該作者
8#
發(fā)表于 2025-3-22 21:44:51 | 只看該作者
Speeding up the Zig-Zag Process,eoretical results and we will present a numerical study on some more practical models than the ones discussed in Vasdekis G. and Roberts G. O. (2023+) [.], showing that the advantages of using SUZZ may also extend to lighter tailed targets.
9#
發(fā)表于 2025-3-23 02:10:57 | 只看該作者
10#
發(fā)表于 2025-3-23 08:32:29 | 只看該作者
 關于派博傳思  派博傳思旗下網站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網 吾愛論文網 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經驗總結 SCIENCEGARD IMPACTFACTOR 派博系數 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網安備110108008328) GMT+8, 2025-10-9 18:24
Copyright © 2001-2015 派博傳思   京公網安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
临沧市| 团风县| 长丰县| 渝北区| 镇宁| 南漳县| 宁城县| 连江县| 广汉市| 杂多县| 乃东县| 永顺县| 武宣县| 大新县| 阿巴嘎旗| 泾川县| 资阳市| 郓城县| 云霄县| 西畴县| 饶河县| 金秀| 会同县| 南昌市| 望谟县| 铁力市| 凤山县| 榆树市| 鲁甸县| 龙游县| 平罗县| 凤台县| 西华县| 嵩明县| 裕民县| 灵山县| 绥江县| 仁化县| 肇庆市| 巴青县| 山东省|