Abstract
The principles of nonlinear principal component analysis and multiple correspondence analysis, which are useful methods for analyzing mixed measurement level data, and related applications are introduced in this book.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 The Author(s)
About this chapter
Cite this chapter
Mori, Y., Kuroda, M., Makino, N. (2016). Introduction. In: Nonlinear Principal Component Analysis and Its Applications. SpringerBriefs in Statistics(). Springer, Singapore. https://doi.org/10.1007/978-981-10-0159-8_1
Download citation
DOI: https://doi.org/10.1007/978-981-10-0159-8_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0157-4
Online ISBN: 978-981-10-0159-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)