EconPapers    
Economics at your fingertips  
 

Test of independence for functional data

Lajos Horvath, Marie Hušková and Gregory Rice

Journal of Multivariate Analysis, 2013, vol. 117, issue C, 100-119

Abstract: We wish to test the null hypothesis that a collection of functional observations are independent and identically distributed. Our procedure is based on the sum of the L2 norms of the empirical correlation functions. The limit distribution of the proposed test statistic is established under the null hypothesis. Under the alternative the sample exhibits serial correlation, and consistency is shown when the sample size as well as the number of lags used in the test statistic tend to ∞. A Monte Carlo study illustrates the small sample behavior of the test and the procedure is applied to data sets, Eurodollar futures and magnetogram records.

Keywords: Variables in Hilbert spaces; Test for independence; Sample autocovariances; Karhunen–Loéve expansion; Asymptotic normality (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X13000195
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:117:y:2013:i:c:p:100-119

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

 
Page updated 2019-08-26
Handle: RePEc:eee:jmvana:v:117:y:2013:i:c:p:100-119