New insights on permutation approach for hypothesis testing on functional data-Reference-Cited by-同舟云学术

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New insights on permutation approach for hypothesis testing on functional data

Published:2014-01-01 Issue:3 Volume:8 Page:339-356
ISSN:1862-5347
Container-title:Advances in Data Analysis and Classification
language:en
Short-container-title:Adv Data Anal Classif

Author:

Corain Livio,Melas Viatcheslav B.,Pepelyshev Andrey,Salmaso Luigi

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s11634-013-0162-2.pdf

Reference32 articles.

1. Bai Z, Saranadasa H (1996) Effect of high dimension: by an example of a two sample problem. Statistica Sinica 6(2):311–329

2. Basso D, Pesarin F, Salmaso L, Solari A (2009) Permutation tests for Stochastic ordering and ANOVA: theory and applications with R. In: Lecture notes in Statistics, Springer, New York, USA

3. Brunner E, Bathke A, Placzek M (2012) Estimation of box’s $$epsilon$$ e p s i l o n for low- and high-dimensional repeated measures designs with unequal covariance matrices. Biometr J 54(3):301–316

4. Cao G, Yang L, Todem D (2012) Simultaneous inference for the mean function based on dense functional data. J Nonparametr Stat 24:359–377

5. Cardot H, Prchal L, Sarda P (2007) No effect and lack-of-fit permutation tests for functional regression. Comput Stat 22:371–390

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