Functional Data Analysis in Biomechanics: A Concise Review of Core Techniques, Applications and Emerging Areas (2024) (SpringerBriefs in Statistics)
By: and and and
Sign Up Now!
Already a Member? Log In
You must be logged into Bookshare to access this title.
Learn about membership options,
or view our freely available titles.
- Synopsis
- This book provides a concise discussion of fundamental functional data analysis (FDA) techniques for analysing biomechanical data, along with an up-to-date review of their applications. The core of the book covers smoothing, registration, visualisation, functional principal components analysis and functional regression, framed in the context of the challenges posed by biomechanical data and accompanied by an extensive case study and reproducible examples using R. This book proposes future directions based on recently published methodological advancements in FDA and emerging sources of data in biomechanics. This is a vibrant research area, at the intersection of applied statistics, or more generally, data science, and biomechanics and human movement research. This book serves as both a contextual literature review of FDA applications in biomechanics and as an introduction to FDA techniques for applied researchers. In particular, it provides a valuable resource for biomechanics researchers seeking to broaden or deepen their FDA knowledge.
- Copyright:
- 2024
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783031688621
- Related ISBNs:
- 9783031688614
- Publisher:
- Springer Nature Switzerland
- Date of Addition:
- 09/23/24
- Copyrighted By:
- The Author
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Sports, Computers and Internet, Mathematics and Statistics, Medicine
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
Reviews
Other Books
- by Edward Gunning
- by John Warmenhoven
- by Andrew J. Harrison
- by Norma Bargary
- in Nonfiction
- in Sports
- in Computers and Internet
- in Mathematics and Statistics
- in Medicine