Statistical Methods for Data Analysis and Decision Sciences (Italian Statistical Society Series on Advances in Statistics) / De Battisti, FrancescaEDT/ Leorato, SamanthaEDT/ Masci, ChiaraEDT

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Statistical Methods for Data Analysis and Decision Sciences (Italian Statistical Society Series on Advances in Statistics)

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Statistical Methods for Data Analysis and Decision Sciences (Italian Statistical Society Series on Advances in Statistics)

De Battisti, FrancescaEDT/ Leorato, SamanthaEDT/ Masci, ChiaraEDT

ウェブストア価格 ¥56,610（本体¥51,464）
Springer, Berlin; Springer（2026/05発売）
外貨定価 EUR 213.99
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製本 Hardcover:ハードカバー版
商品コード 9783032189875

Full Description

This volume on statistical methods for data analysis and decision sciences showcases the interplay between statistics and data science, reflecting a broad spectrum of data-driven challenges, innovative approaches, methodological developments and applications. It gathers peer-reviewed short papers presented at the 3rd Conference of the Statistics and Data Science Group of the Italian Statistical Society, SDS 2025, held in Milan, Italy, April 2-3, 2025.

The papers cover a wide variety of topics focused on modeling and analyzing complex data, including structured, non-structured and mixed data, offering fresh perspectives tailored to diverse research goals. The contributions propose innovative methods and approaches in causal inference, sampling and big data, Bayesian methods, functional data analysis, unsupervised learning, robust statistics and penalized regression, spatio-temporal methods, clustering, time series analysis, text analysis and image processing. A wide range of applications in several areas are presented, including environmental issues and sustainability, earth and geohazards, official statistics, social issues and inequality, health informatics, medicine, health and well-being, statistical process monitoring, financial statistics and econometrics, and artificial intelligence, addressing matters of particular relevance for sustainable development, including Sustainable Development Goals (SDGs) 1, 3, 5, 7, and 13, among others.

Invited Sessions.- Subsampling from Big Data.- Data Science for Official Statistics.- Specialized Sessions.- Causal Inference.- Bayesian Data Science.- NLP based methods for Medical documents.- Distributional and functional data analysis.- ENBIS session: advances in statistical process monitoring and temporal clustering.- Graspa session - Environmental issues and sustainability.- Social Data Science: Relational and structured Data.- Advances in Explainable AI.- Cladag session- Unsupervised learning for complex data.- Contributed Sessions.- Spatio-Temporal Methods In Environmental Analysis.- Text Analysis & Image Processing.- Financial Statistics & Econometrics.- Omic Data & Health Informatics.- Advanced Methodology.- Statistics and data science for health & well-being.- Statistical approaches to gender & education unbalance.- Methods and models for earth & geohazards.- Time & Clustering in Environmental Studies.- Society & Social Behavior Analysis.- Bayesian Methods & Applications.- Robustness & Penalization Methods.- Advanced Methods in Causal Analysis.- Time Series Analysis.- AI Methods for Data Processing and Risk Analysis.