New Springer Contributions to Statistics- New Trends in Functional Statistics and Related Fields

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.

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.