Jin-Ting Zhang

Analysis of Variance for Functional Data (eBook, PDF)

• Format: PDF

Produktbeschreibung

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 functional observations, functional ANOVA, functional linear models with functional responses, ill-conditioned functional linear models, diagnostics of functional observations, heteroscedastic ANOVA for functional data, and testing equality of covariance functions. Data sets and MATLAB are available on the author's website.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 412
• Erscheinungstermin: 18. Juni 2013
• Englisch
• ISBN-13: 9781439862742
• Artikelnr.: 40065777

Autorenporträt

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.