Department of Mathematics
Motivated by an ischemic heart screening problem, a new global test for one-way ANOVA in functional data analysis is studied. The test statistic is taken as the maximum of the pointwise F-test statistic over the interval the functional responses are observed. Nonparametric bootstrap, which is applicable in more general situations and easier to implement than parametric bootstrap, is employed to approximate the null distribution and to obtain an approximate critical value. Under mild conditions, asymptotically our test has the correct level and is root-n consistent in detecting local alternatives. Simulation studies show that the proposed test outperforms several existing tests in terms of both size control and power when the correlation between observations at any two different points is high or moderate, and it is comparable with the competitors otherwise. Application to an ischemic heart dataset suggests that resting electrocardiogram signals may contain enough information for ischemic heart screening at outpatient clinics, without the help of stress tests required by the current standard procedure.
Functional hypothesis testing, Functional data, Local power, Nonparametric bootstrap, Smoothing and nonparametric regression
Source Publication Title
Computational Statistics and Data Analysis
Link to Publisher's Edition
Zhang, J., Cheng, M., Wu, H., & Zhou, B. (2019). A new test for functional one-way ANOVA with applications to ischemic heart screening. Computational Statistics and Data Analysis, 132, 3-17. https://doi.org/10.1016/j.csda.2018.05.004
Available for download on Saturday, May 01, 2021