Functional and High-Dimensional Statistics and Related Fields

The book presents the latest research on statistical analysis of functional, high-dimensional, and complex data, covering methodological and computational aspects, and real-world applications. It includes topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis. The book was originally to be held at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic, but had to be postponed due to the COVID-19 pandemic.

Format: Paperback / softback
Length: 254 pages
Publication date: 21 June 2021
Publisher: Springer Nature Switzerland AG

This comprehensive book delves into the latest advancements in statistical analysis, particularly focusing on functional, high-dimensional, and complex data. It encompasses a wide range of methodological and computational aspects, as well as real-world applications. The book explores diverse topics such as classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operational statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis. Furthermore, it includes applications in various fields such as automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics, and urban environments.

The book is a valuable resource for researchers, practitioners, and students interested in functional statistics and its applications. It comprises selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS), which was originally scheduled to take place in Brno, Czech Republic, in June 2020. However, due to the COVID-19 pandemic, the workshop was postponed. The IWFOS workshops, initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, serve as a platform for discussing the latest trends and advancements in functional statistics and related fields. These workshops foster the exchange of ideas and international collaboration, making them crucial for advancing the field.

The book is organized into nine chapters, each authored by experts in the field. The chapters cover various aspects of statistical analysis, including theoretical foundations, computational techniques, and practical applications. The authors provide detailed explanations and examples to illustrate their points, making the content accessible to a broad audience.

One of the key strengths of the book is its comprehensive coverage of functional data analysis. Functional data analysis is a growing field that deals with data that are not necessarily continuous or normally distributed. It involves the use of non-parametric and semi-parametric methods to analyze these data, which are often encountered in various scientific and engineering applications. The book provides an in-depth introduction to functional data analysis, covering topics such as density estimation, smoothing, and inference on functional data.

Another notable feature of the book is its emphasis on real-world applications. The authors showcase how statistical analysis can be applied to solve practical problems in various fields. For instance, in the automobile engineering chapter, the authors discuss the use of statistical models to predict vehicle performance and reliability. In the criminology chapter, the authors explore the use of statistical methods to analyze crime data and identify patterns and trends.

The book also includes several case studies and examples to illustrate the practical applications of statistical analysis. These case studies provide real-world context and help readers understand how statistical methods can be used to address real-world problems.

In conclusion, this book is a valuable resource for anyone interested in statistical analysis, particularly in the field of functional, high-dimensional, and complex data. It provides a comprehensive overview of the latest research and advancements in the field, covering theoretical foundations, computational techniques, and practical applications. The book's emphasis on real-world applications and its inclusion of case studies and examples make it an invaluable tool for researchers, practitioners, and students alike.

Weight: 454g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030477585
Edition number: 1st ed. 2020