找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: New Statistical Developments in Data Science; SIS 2017, Florence, Alessandra Petrucci,Filomena Racioppi,Rosanna Verd Conference proceeding

[复制链接]
查看: 26782|回复: 59
发表于 2025-3-21 18:22:41 | 显示全部楼层 |阅读模式
书目名称New Statistical Developments in Data Science
副标题SIS 2017, Florence,
编辑Alessandra Petrucci,Filomena Racioppi,Rosanna Verd
视频video
概述Highlights key statistical methods and recent contributions to data science.Shows how Statistics and Data Analysis techniques can support business operations and provide essential information for deci
丛书名称Springer Proceedings in Mathematics & Statistics
图书封面Titlebook: New Statistical Developments in Data Science; SIS 2017, Florence,  Alessandra Petrucci,Filomena Racioppi,Rosanna Verd Conference proceeding
描述.This volume collects the extended versions of papers presented at the SIS Conference “Statistics and Data Science: new challenges, new generations”, held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science, the contributions offer an essential overview of the latest developments in various areas of statistics research. The 35 contributions have been divided into six parts, each of which focuses on a core area contributing to “Data Science”.  The book covers topics including strong statistical methodologies, Bayesian approaches, applications in population and social studies, studies in economics and finance, techniques of sample design and mathematical statistics. Though the book is mainly intended for researchers interested in the latest frontiers of Statistics and Data Analysis, it also offers valuable supplementary material for students of the disciplines dealt withhere. Lastly, it will help Statisticians and Data Scientists recognize their counterparts’ fundamental role..
出版日期Conference proceedings 2019
关键词Data Science; Big Data; Data Analysis; Knowledge Based Methods; Complex Data Analytics; Proceedings; Machi
版次1
doihttps://doi.org/10.1007/978-3-030-21158-5
isbn_softcover978-3-030-21160-8
isbn_ebook978-3-030-21158-5Series ISSN 2194-1009 Series E-ISSN 2194-1017
issn_series 2194-1009
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

书目名称New Statistical Developments in Data Science影响因子(影响力)




书目名称New Statistical Developments in Data Science影响因子(影响力)学科排名




书目名称New Statistical Developments in Data Science网络公开度




书目名称New Statistical Developments in Data Science网络公开度学科排名




书目名称New Statistical Developments in Data Science被引频次




书目名称New Statistical Developments in Data Science被引频次学科排名




书目名称New Statistical Developments in Data Science年度引用




书目名称New Statistical Developments in Data Science年度引用学科排名




书目名称New Statistical Developments in Data Science读者反馈




书目名称New Statistical Developments in Data Science读者反馈学科排名




单选投票, 共有 0 人参与投票
 

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

您所在的用户组没有投票权限
发表于 2025-3-22 00:17:08 | 显示全部楼层
发表于 2025-3-22 02:38:20 | 显示全部楼层
发表于 2025-3-22 08:14:53 | 显示全部楼层
Sample Design for the Integration of Population Census and Social Surveys Il Disegno Campionario perveys. The aim of this work is to compare two sampling strategies for the census survey sample. The first comprises pooling together the samples of the main social surveys, while the second consists of an ad hoc sampling design. Different estimation procedures are taken into account in order to compare the two sampling strategies.
发表于 2025-3-22 08:46:00 | 显示全部楼层
发表于 2025-3-22 14:36:05 | 显示全部楼层
Conference proceedings 2019held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science, the contributions offer an essential overview of the latest developments in various areas of statistics research. The 35 contributions have been divided into
发表于 2025-3-22 20:13:19 | 显示全部楼层
Text Mining and Big Textual Data: Relevant Statistical Modelsxpression: correlation is not causation. Application areas are: quantitative and also qualitative assessment, narrative analysis and assessing impact, and baselining and contextualizing, statistically and in related aspects such as visualization.
发表于 2025-3-23 01:14:30 | 显示全部楼层
发表于 2025-3-23 03:43:07 | 显示全部楼层
Monitoring the Spatial Correlation Among Functional Data Streams Through Moran’s Indexed data are more likely to be similar when measured at nearby locations rather than in distant places. In order to monitor such correlation over time and to deal with huge amount of data, we propose a strategy based on computing the well known Moran’s index and Geary’s index on summaries of the data.
发表于 2025-3-23 09:16:32 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-11 03:15
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表