TY - JOUR
T1 - Two samples tests for functional data
AU - Zhang, Chongqi
AU - Peng, Heng
AU - Zhang, Jin Ting
N1 - Funding Information:
Chongqi Zhang’s research is supported by NNSF of China 10871054, and Heng Peng’s research is supported by the CERG grant of Hong Research Grant Council, HKBU 201707 and the FRG grant of Hong Kong Baptist University, FRG/06-07/II-14.
PY - 2010/1
Y1 - 2010/1
N2 - Data in many experiments arises as curves and therefore it is natural to use a curve as a basic unit in the analysis, which is in terms of functional data analysis (FDA). Functional curves are encountered when units are observed over time. Although the whole function curve itself is not observed, a sufficiently large number of evaluations, as is common with modern recording equipment, is assumed to be available. In this article, we consider the statistical inference for the mean functions in the two samples problem drawn from functional data sets, in which we assume that functional curves are observed, that is, we consider the test if these two groups of curves have the same mean functional curve when the two groups of curves without noise are observed. The L2-norm based and bootstrap-based test statistics are proposed. It is shown that the proposed methodology is flexible. Simulation study and real-data examples are used to illustrate our techniques.
AB - Data in many experiments arises as curves and therefore it is natural to use a curve as a basic unit in the analysis, which is in terms of functional data analysis (FDA). Functional curves are encountered when units are observed over time. Although the whole function curve itself is not observed, a sufficiently large number of evaluations, as is common with modern recording equipment, is assumed to be available. In this article, we consider the statistical inference for the mean functions in the two samples problem drawn from functional data sets, in which we assume that functional curves are observed, that is, we consider the test if these two groups of curves have the same mean functional curve when the two groups of curves without noise are observed. The L2-norm based and bootstrap-based test statistics are proposed. It is shown that the proposed methodology is flexible. Simulation study and real-data examples are used to illustrate our techniques.
KW - Bootstrap-based test statistic
KW - Functional data
KW - Hypothesis test
KW - L2-norm-based test statistic
UR - http://www.scopus.com/inward/record.url?scp=76949107468&partnerID=8YFLogxK
U2 - 10.1080/03610920902755839
DO - 10.1080/03610920902755839
M3 - Journal article
AN - SCOPUS:76949107468
SN - 0361-0926
VL - 39
SP - 559
EP - 578
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 4
ER -