Features:
- Functional regression models receive a modern treatment that allows extensions to many practical scenarios and development of state-of-the-art software
- The connection between functional regression, penalized smoothing, and mixed effects models is used as the cornerstone for inference
- Multilevel, longitudinal, and structured functional data are discussed with emphasis on emerging functional data structures
- Methods for clustering functional data before and after smoothing are discussed
- Multiple new functional data sets with dense and sparse sampling designs from various application areas are presented, including the NHANES linked accelerometry and mortality data, COVID-19 mortality data, CD4 counts data and the CONTENT child growth study
- Step-by-step software implementations are included, along with a supplementary website (www.FunctionalDataAnalysis.com) featuring software, data, and tutorials
- More than 100 plots for visualization of functional data are presented
Functional Data Analysis with R is primarily aimed at undergraduate, master's and PhD students, as well as data scientists and researchers working on functional data analysis. The book can be read at different levels and combines state-of-the-art software, methods, and inference. It can be used for self-learning, teaching, and research, and will particularly appeal to anyone who is interested in practical methods for hands-on, problem-forward functional data analysis. The reader should have some basic coding experience, but expertise in R is not required.
Features:
- Functional regression models receive a modern treatment that allows extensions to many practical scenarios and development of state-of-the-art software
- The connection between functional regression, penalized smoothing, and mixed effects models is used as the cornerstone for inference
- Multilevel, longitudinal, and structured functional data are discussed with emphasis on emerging functional data structures
- Methods for clustering functional data before and after smoothing are discussed
- Multiple new functional data sets with dense and sparse sampling designs from various application areas are presented, including the NHANES linked accelerometry and mortality data, COVID-19 mortality data, CD4 counts data and the CONTENT child growth study
- Step-by-step software implementations are included, along with a supplementary website (www.FunctionalDataAnalysis.com) featuring software, data, and tutorials
- More than 100 plots for visualization of functional data are presented
Functional Data Analysis with R is primarily aimed at undergraduate, master's and PhD students, as well as data scientists and researchers working on functional data analysis. The book can be read at different levels and combines state-of-the-art software, methods, and inference. It can be used for self-learning, teaching, and research, and will particularly appeal to anyone who is interested in practical methods for hands-on, problem-forward functional data analysis. The reader should have some basic coding experience, but expertise in R is not required.

Functional Data Analysis with R
338
Functional Data Analysis with R
338Hardcover
Product Details
ISBN-13: | 9781032244716 |
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Publisher: | CRC Press |
Publication date: | 03/11/2024 |
Series: | Chapman & Hall/CRC Monographs on Statistics and Applied Probability |
Pages: | 338 |
Product dimensions: | 7.00(w) x 10.00(h) x (d) |