J 2012

Dispersion operators and resistant second-order functional data analysis

KRAUS, David a Victor M. PANARETOS

Základní údaje

Originální název

Dispersion operators and resistant second-order functional data analysis

Autoři

KRAUS, David a Victor M. PANARETOS

Vydání

Biometrika, Oxford, Oxford Univ Press, 2012, 0006-3444

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 1.650

DOI

UT WoS

000311303800005

Klíčová slova anglicky

Covariance operator; Karhunen-Loeve expansion; M-estimation; Resistant test; Spectral truncation; Two-sample testing

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 12. 1. 2016 16:23, doc. Mgr. David Kraus, Ph.D.

Anotace

V originále

Inferences related to the second-order properties of functional data, as expressed by covariance structure, can become unreliable when the data are non-Gaussian or contain unusual observations. In the functional setting, it is often difficult to identify atypical observations, as their distinguishing characteristics can be manifold but subtle. In this paper, we introduce the notion of a dispersion operator, investigate its use in probing the second-order structure of functional data, and develop a test for comparing the second-order characteristics of two functional samples that is resistant to atypical observations and departures from normality. The proposed test is a regularized M-test based on a spectrally truncated version of the Hilbert-Schmidt norm of a score operator defined via the dispersion operator. We derive the asymptotic distribution of the test statistic, investigate the behaviour of the test in a simulation study and illustrate the method on a structural biology dataset.