New Trends in Functional Statistics and Related Fields (eng)
Language: English
Published by Springer, 2025
- Hardcover
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- Title
- New Trends in Functional Statistics and Related Fields (eng)
- Author
- Aneiros, Germán
- Publisher
- Springer
- Publication year
- 2025
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3031923820
- ISBN 13
- 9783031923821
This volume gathers peer-reviewed contributions presented at the 6th International Workshop on Functional and Operatorial Statistics, IWFOS 2025, held in Novara, Italy, June 25-27, 2025.
Covering a broad spectrum of topics in functional and operatorial statistics and related fields, including high-dimensional statistics and machine learning, the contributions tackle both fundamental theoretical challenges and practical applications. A variety of features of statistics for functional data are addressed, such as estimation of functional features, exploration and pre-processing of functional data, methodologies for functional regression and forecasting problems, unsupervised and supervised classification, and testing procedures. Nonstandard functional data and situations which go beyond the pattern of samples of independent variables are investigated, and a link to the field of artificial intelligence is presented. Interesting real data applications to medicine, health, economics and the natural, environmental and social sciences are featured throughout.
Initiated at the University of Toulouse in 2008, the series of IWFOS workshops fosters discussion and international collaboration on theoretical advancements, methodological innovations, and applications in functional and operatorial statistics and related fields.
Chapter 42 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
"Synopsis" may belong to another edition of this title.
About the Author
Germán Aneiros is a Full Professor of Statistics at the University of A Coruña, Spain. His main research interest focuses on scalar-on-function regression models, covering linear, nonparametric, partial linear and single index regression. His interests also include the case of high-dimensional covariates. He is an Associate Editor of the journals Computational Statistics and Journal of Multivariate Analysis.
Enea G. Bongiorno is an Associate Professor in Statistics at Università del Piemonte Orientale in Novara, Italy. His interests include non- and semi-parametric methods and small ball probability for functional data. He is a fellow of the Bernoulli Society, and IASC (International Association for Statistical Computing) of which he was scientific secretary of the European Regional Section and on the board of directors. He is an Associate Editor of the journals Computational Statistics & Data Analysis and Computational Statistics.
Aldo Goia is a Full Professor of Statistics at Università del Piemonte Orientale in Novara, Italy. His research focuses on statistical methods for functional data and in particular on non-parametric and semi-parametric regression models, the small ball probability factorization and the study of complexity. He is an Associate Editor of the journal Computational Statistics.
Marie Hušková is a Full Professor of Mathematical Statistics at Charles University in Prague, Czech Republic. She is the author of more than 130 scientific papers, mainly on asymptotic statistics, nonparametric and multivariate statistics and change-point problems. She is an Associate Editor of the journals Metrika, Statistics, and Sequential Analysis, and is a former Associate Editor of the Journal of Statistical Planning and Inference and REVSTAT. She is an elected member of ISI and a fellow of IMS. For several years, she was the Chair of the European Regional Committee of the Bernoulli Society and a member of the Council of ISI.
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