Analysis of Variance for Functional Data

This self-contained book presents up-to-date hypothesis testing methods for functional data analysis. Useful for statistical researchers and practitioners analyzing functional data, it gives both a theoretical and applied treatment of functional data analysis supported by easy-to-use MATLAB® code. The book covers the reconstruction of

List of contents

Introduction. Nonparametric Smoothers for a Single Curve. Reconstruction of Functional Data. Stochastic Processes. ANOVA for Functional Data. Linear Models with Functional Responses. Ill-Conditioned Functional Linear Models. Diagnostics of Functional Observations. Heteroscedastic ANOVA for Functional Data. Test of Equality of Covariance Functions. Bibliography. Index.

About the author

Jin-Ting Zhang is an associate professor in the Department of Statistics and Applied Probability at the National University of Singapore. He has published extensively and has served on the editorial boards of several international statistical journals. He is the coauthor of Nonparametric Regression Methods for Longitudinal Data Analysis: Mixed-Effect Modelling Approaches and the coeditor of Advances in Statistics: Proceedings of the Conference in Honor of Professor Zhidong Bai on His 65th Birthday.

Summary

This self-contained book presents up-to-date hypothesis testing methods for functional data analysis. Useful for statistical researchers and practitioners analyzing functional data, it gives both a theoretical and applied treatment of functional data analysis supported by easy-to-use MATLAB® code. The book covers the reconstruction of

Product details

• Authors: Jin-Ting Zhang, Zhang Jin-Ting
• Publisher: Taylor and Francis
• Languages: English
• Product format: Paperback / Softback
• Released: 14.10.2024
• EAN: 9781032920399
• ISBN: 978-1-032-92039-9
• No. of pages: 410
• Weight: 453 g
• Illustrations: schwarz-weiss Illustrationen
• Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; MATHEMATICS / Probability & Statistics / General, Biology, life sciences, Probability & statistics, Probability and statistics