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Two-sample Testing for Mean Functions with Incompletely Observed Functional Data
Acta Mathematicae Applicatae Sinica, English Series ( IF 0.8 ) Pub Date : 2020-03-01 , DOI: 10.1007/s10255-020-0934-3
Yan-qiu Zhou , Yan-ling Wan , Tao Zhang

In functional data analysis, the collected data are often assumed to be fully observed on the domain. However, in dealing with real data (for example, environmental pollution data), we are often faced with the scenario that some functional data are fully observed on dense lattice while others are incompletely observed. In this paper, we propose a method for testing equivalence of mean functions of two samples under this scenario. Some asymptotic results of the proposed methods are established. The proposed test is employed to analyze an environmental pollution study in Liuzhou City of China. Simulations show that the proposed test has a good control of the type-I error, and is more powerful than the complete case test in most cases.
更新日期:2020-03-01
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